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blog: Initial.

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  1. .gitattributes +1 -0
  2. Dockerfile +17 -0
  3. LICENSE +13 -0
  4. README.md +11 -0
  5. index.html +20 -0
  6. package.json +43 -0
  7. post/addressing selinux denials in android development.md +426 -0
  8. post/cicada 3301.md +386 -0
  9. post/hf.md +869 -0
  10. post/learning the basics of c programming.md +218 -0
  11. post/llm bias and hallucinations.md +868 -0
  12. post/llm limitations.md +780 -0
  13. post/mwb.md +530 -0
  14. post/why the linux kernel uses c and not cpp.md +227 -0
  15. public/assets/images/favicon.ico +0 -0
  16. public/assets/images/profile.png +3 -0
  17. src/client/App.tsx +22 -0
  18. src/client/components/blog/PostCard.tsx +98 -0
  19. src/client/components/blog/PostContent.tsx +131 -0
  20. src/client/components/blog/PostList.tsx +42 -0
  21. src/client/components/common/Head.tsx +46 -0
  22. src/client/components/layout/Footer.tsx +53 -0
  23. src/client/components/layout/Header.tsx +60 -0
  24. src/client/components/layout/Layout.tsx +36 -0
  25. src/client/hooks/usePosts.ts +84 -0
  26. src/client/main.tsx +24 -0
  27. src/client/pages/HomePage.tsx +84 -0
  28. src/client/pages/PostPage.tsx +91 -0
  29. src/client/styles/global.css +387 -0
  30. src/server/index.ts +64 -0
  31. src/server/routes/apiRoutes.ts +85 -0
  32. src/server/services/postService.ts +94 -0
  33. src/server/utils/fileWatcher.ts +69 -0
  34. src/server/utils/markdownParser.ts +49 -0
  35. src/shared/config.ts +37 -0
  36. src/shared/types.ts +33 -0
  37. tsconfig.json +37 -0
  38. tsconfig.node.json +12 -0
  39. tsconfig.server.json +28 -0
  40. vite.config.ts +35 -0
.gitattributes ADDED
@@ -0,0 +1 @@
 
 
1
+ public/assets/images/profile.png filter=lfs diff=lfs merge=lfs -text
Dockerfile ADDED
@@ -0,0 +1,17 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ #
2
+ # SPDX-FileCopyrightText: Hadad <hadad@linuxmail.org>
3
+ # SPDX-License-Identifier: Apache-2.0
4
+ #
5
+
6
+ FROM node:20-alpine
7
+
8
+ WORKDIR /app
9
+
10
+ COPY . .
11
+
12
+ RUN npm install \
13
+ && npm run build
14
+
15
+ EXPOSE 3000
16
+
17
+ CMD ["npm", "start"]
LICENSE ADDED
@@ -0,0 +1,13 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Copyright (c) 2025 Hadad <hadad@linuxmail.org>
2
+
3
+ Licensed under the Apache License, Version 2.0 (the "License");
4
+ you may not use this file except in compliance with the License.
5
+ You may obtain a copy of the License at
6
+
7
+ http://www.apache.org/licenses/LICENSE-2.0
8
+
9
+ Unless required by applicable law or agreed to in writing, software
10
+ distributed under the License is distributed on an "AS IS" BASIS,
11
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12
+ See the License for the specific language governing permissions and
13
+ limitations under the License.
README.md ADDED
@@ -0,0 +1,11 @@
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ title: Personal Blog
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+ short_description: Coretan Kecil
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+ license: apache-2.0
5
+ emoji: 📚
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+ colorFrom: blue
7
+ colorTo: blue
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+ sdk: docker
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+ app_port: 3000
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+ pinned: false
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+ ---
index.html ADDED
@@ -0,0 +1,20 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ <!--
2
+ SPDX-FileCopyrightText: Hadad <hadad@linuxmail.org>
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+ SPDX-License-Identifier: Apache-2.0
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+ -->
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+
6
+ <!DOCTYPE html>
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+ <html lang="en">
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+ <head>
9
+ <meta charset="UTF-8" />
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+ <meta name="viewport" content="width=device-width, initial-scale=1.0, maximum-scale=5.0, minimum-scale=1.0" />
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+ <meta name="description" content="Personal Blog" />
12
+ <meta name="theme-color" content="#ffffff" />
13
+ <link rel="icon" type="image/x-icon" href="/assets/images/favicon.ico" />
14
+ <title>Hadad Darajat</title>
15
+ </head>
16
+ <body>
17
+ <div id="root"></div>
18
+ <script type="module" src="/src/client/main.tsx"></script>
19
+ </body>
20
+ </html>
package.json ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "name": "personal-blog",
3
+ "version": "0.0.0",
4
+ "private": true,
5
+ "author": "Hadad Darajat",
6
+ "type": "module",
7
+ "scripts": {
8
+ "dev": "concurrently \"npm run dev:server\" \"npm run dev:client\"",
9
+ "dev:client": "vite",
10
+ "dev:server": "tsx watch src/server/index.ts",
11
+ "build": "npm run build:client && npm run build:server",
12
+ "build:client": "vite build",
13
+ "build:server": "tsc -p tsconfig.server.json",
14
+ "start": "node dist/server/index.js",
15
+ "preview": "npm run build && npm run start"
16
+ },
17
+ "dependencies": {
18
+ "chokidar": "^3.6.0",
19
+ "cors": "^2.8.5",
20
+ "express": "^4.21.0",
21
+ "front-matter": "^4.0.2",
22
+ "highlight.js": "^11.10.0",
23
+ "lucide-react": "^0.454.0",
24
+ "marked": "^14.1.2",
25
+ "marked-highlight": "^2.1.4",
26
+ "react": "^18.3.1",
27
+ "react-dom": "^18.3.1",
28
+ "react-helmet-async": "^2.0.5",
29
+ "react-router-dom": "^6.27.0"
30
+ },
31
+ "devDependencies": {
32
+ "@types/cors": "^2.8.17",
33
+ "@types/express": "^4.17.21",
34
+ "@types/node": "^22.7.5",
35
+ "@types/react": "^18.3.11",
36
+ "@types/react-dom": "^18.3.1",
37
+ "@vitejs/plugin-react": "^4.3.2",
38
+ "concurrently": "^9.0.1",
39
+ "tsx": "^4.19.1",
40
+ "typescript": "^5.6.3",
41
+ "vite": "^5.4.9"
42
+ }
43
+ }
post/addressing selinux denials in android development.md ADDED
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1
+ ---
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+ title: Addressing SELinux Denials in Android Development
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+ date: 2025-01-30
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+ description: Security Enhanced Linux, commonly known as SELinux, has become an integral part of Android's security architecture since Android 4.3. For developers working on AOSP or proprietary Android systems, understanding and properly addressing SELinux denials is crucial. This comprehensive guide explores what SELinux is, why it matters in Android, and how to effectively handle SELinux policies during development.
5
+ author: Hadad Darajat
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+ tags:
7
+ - android
8
+ - selinux
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+ - sepolicy
10
+ ---
11
+
12
+ <p>
13
+ Security Enhanced Linux, commonly known as SELinux, has become an integral part of Android's security architecture since Android 4.3. For developers working on AOSP or proprietary Android systems, understanding and properly addressing SELinux denials is crucial. This comprehensive guide explores what SELinux is, why it matters in Android, and how to effectively handle SELinux policies during development.
14
+ </p>
15
+
16
+ <h2>Understanding SELinux</h2>
17
+
18
+ <p>
19
+ SELinux is a mandatory access control mechanism originally developed by the National Security Agency. Unlike traditional discretionary access control systems where users and processes can decide who has access to their resources, SELinux enforces security policies at the kernel level that cannot be bypassed by user space applications or even root processes.
20
+ </p>
21
+
22
+ <p>
23
+ In traditional Linux systems, processes run with the user ID and group ID of the user who started them. If a process runs as root, it has unlimited access to the entire system. This model is inherently vulnerable because if an attacker compromises a privileged process, they gain complete system control. SELinux adds an additional layer of protection by defining exactly what each process can and cannot do, regardless of its user ID.
24
+ </p>
25
+
26
+ <p>
27
+ SELinux operates on the principle of least privilege. Every process runs in a specific security context, and policies explicitly define what resources that context can access. If an operation is not explicitly allowed by policy, it is denied. This default deny approach significantly reduces the attack surface of the system.
28
+ </p>
29
+
30
+ <h2>SELinux in the Android Ecosystem</h2>
31
+
32
+ <p>
33
+ Google began integrating SELinux into Android starting with version 4.3 in 2013, initially in permissive mode for testing. By Android 5.0, SELinux enforcement became mandatory for all devices. This integration was driven by the need to strengthen Android's security posture against increasingly sophisticated attacks.
34
+ </p>
35
+
36
+ <p>
37
+ Android's SELinux implementation is tailored specifically for mobile devices. While desktop Linux distributions often have thousands of policy rules, Android maintains a more focused set of policies designed around its app sandbox model. Every Android app runs in its own security context, isolated from other apps and from system components.
38
+ </p>
39
+
40
+ <p>
41
+ The Android security model relies on several layers of protection. App sandboxing provides process isolation, permissions control what resources apps can access, and SELinux enforces that even system components and privileged processes operate within defined boundaries. This defense in depth approach means that even if one security layer is breached, others remain to prevent full system compromise.
42
+ </p>
43
+
44
+ <p>
45
+ In AOSP development, SELinux policies are defined in the system/sepolicy directory. Device manufacturers and custom ROM developers often need to extend these policies with vendor specific or device specific rules. Understanding how to properly write and maintain these policies is essential for anyone working on Android platform development.
46
+ </p>
47
+
48
+ <h2>The Benefits of SELinux on Android</h2>
49
+
50
+ <p>
51
+ The most significant benefit of SELinux is containment. If a vulnerability is exploited in one component, SELinux limits what the attacker can do. For example, if the media server process is compromised, SELinux policies prevent the attacker from accessing user data, modifying system files, or executing arbitrary code in other processes. The breach is contained to the compromised process.
52
+ </p>
53
+
54
+ <p>
55
+ SELinux provides protection against privilege escalation attacks. Even if an attacker gains root access through an exploit, they are still constrained by SELinux policies. They cannot arbitrarily read sensitive files, modify system partitions, or interfere with other security critical processes. This dramatically raises the bar for successful attacks.
56
+ </p>
57
+
58
+ <p>
59
+ For enterprise and government users, SELinux provides assurance that devices meet security compliance requirements. The mandatory access control model aligns with security frameworks like Common Criteria and FIPS. Organizations can deploy Android devices with confidence that strong security policies are enforced at the kernel level.
60
+ </p>
61
+
62
+ <p>
63
+ SELinux also helps developers identify security issues during development. When properly configured, SELinux denials highlight when code is trying to access resources it should not. This serves as an early warning system for potential security vulnerabilities or architectural problems in the software design.
64
+ </p>
65
+
66
+ <h2>The Dangers of Misconfigured SELinux</h2>
67
+
68
+ <p>
69
+ Setting SELinux to permissive mode globally is one of the most common and dangerous mistakes in Android development. In permissive mode, SELinux logs policy violations but does not enforce them. Developers sometimes do this to avoid dealing with denials during development, but it completely negates the security benefits of SELinux.
70
+ </p>
71
+
72
+ <p>
73
+ A device shipping with SELinux in permissive mode is fundamentally insecure. All the careful work that went into designing security boundaries and limiting process capabilities is rendered useless. Exploits that would normally be contained can now escalate to full system compromise. For commercial devices, this also violates Android compatibility requirements and can result in failing CTS tests.
74
+ </p>
75
+
76
+ <p>
77
+ Writing overly permissive policies is another common problem. Adding blanket permissions like allowing a domain to read all files or execute in all domains defeats the purpose of SELinux. Each permission should be carefully considered and justified. Policies should grant the minimum necessary access for functionality, nothing more.
78
+ </p>
79
+
80
+ <p>
81
+ Improperly labeled files and processes can create security holes. If a sensitive file is labeled with a generic type that many processes can access, it is no longer protected. Similarly, if a privileged process runs in a context that is too permissive, vulnerabilities in that process can be easily exploited.
82
+ </p>
83
+
84
+ <p>
85
+ Ignoring SELinux denials during development and then trying to fix them all at once before release is a recipe for problems. This approach often leads to rushed, overly permissive policies that introduce security vulnerabilities. SELinux policies should be developed incrementally alongside the code, with each denial carefully analyzed and addressed appropriately.
86
+ </p>
87
+
88
+ <h2>Enforcing vs Permissive Mode</h2>
89
+
90
+ <p>
91
+ SELinux can operate in three modes globally or per domain. Enforcing mode actively blocks operations that violate policy and logs the denials. Permissive mode allows all operations but logs what would have been denied. Disabled mode turns off SELinux entirely, though this is not supported on modern Android devices.
92
+ </p>
93
+
94
+ <p>
95
+ In enforcing mode, the system is secure but developers must ensure policies are correct. Any legitimate operation that is not explicitly allowed will be blocked, potentially breaking functionality. This requires careful policy development and testing to ensure all necessary permissions are granted while maintaining security.
96
+ </p>
97
+
98
+ <p>
99
+ Permissive mode is useful during initial development to identify what policies are needed without breaking functionality. You can run your code, collect the denials from the logs, and use them to write appropriate policies. However, permissive mode should only be used temporarily in development environments, never in production.
100
+ </p>
101
+
102
+ <p>
103
+ Android allows setting permissive mode per domain rather than globally. This is useful when bringing up a new component. You can set just that component's domain to permissive while keeping the rest of the system in enforcing mode. This provides a middle ground that maintains overall system security while allowing development work to proceed.
104
+ </p>
105
+
106
+ <p>
107
+ The command to check SELinux mode is simple. You can use adb shell getenforce to see if the system is in enforcing or permissive mode globally. To set permissive mode for testing, use adb shell setenforce 0, though this requires root access and should only be done on development devices.
108
+ </p>
109
+
110
+ ```bash
111
+ adb shell getenforce
112
+ adb shell setenforce 0 # Set to permissive (development only)
113
+ adb shell setenforce 1 # Set to enforcing
114
+ ```
115
+
116
+ <p>
117
+ For per domain permissive mode during development, you can add the permissive attribute to a domain in your policy files. Remember to remove this before production builds.
118
+ </p>
119
+
120
+ <h2>Understanding SELinux Denials</h2>
121
+
122
+ <p>
123
+ When SELinux denies an operation, it generates an AVC denial message in the kernel log. AVC stands for Access Vector Cache, the component that caches policy decisions. These denial messages contain all the information needed to understand what was blocked and why.
124
+ </p>
125
+
126
+ <p>
127
+ A typical denial message looks like this when viewed through logcat or dmesg.
128
+ </p>
129
+
130
+ ```bash
131
+ avc: denied { read write } for pid=1234 comm="mediaserver"
132
+ name="video0" dev="tmpfs" ino=5678
133
+ scontext=u:r:mediaserver:s0
134
+ tcontext=u:object_r:device:s0
135
+ tclass=chr_file permissive=0
136
+ ```
137
+
138
+ <p>
139
+ Breaking down this denial message reveals the complete picture. The denied actions are read and write. The source context is mediaserver domain, trying to operate on a file labeled with the device type. The target class is chr_file meaning a character device file. The process ID and executable name help identify exactly which code triggered the denial.
140
+ </p>
141
+
142
+ <p>
143
+ To collect denials during testing, you can use logcat with appropriate filtering. The following command shows only SELinux related messages.
144
+ </p>
145
+
146
+ ```bash
147
+ adb logcat | grep avc
148
+ adb shell dmesg | grep avc
149
+ ```
150
+
151
+ <p>
152
+ For more comprehensive analysis, Android provides the audit2allow tool that can parse denial logs and suggest policy rules. However, you should not blindly apply its suggestions. Each rule should be reviewed to ensure it does not grant excessive permissions.
153
+ </p>
154
+
155
+ <h2>Writing SELinux Policies for Android</h2>
156
+
157
+ <p>
158
+ SELinux policies in Android are written in a domain specific language. Policies are organized into type enforcement files with the te extension, file context files with the fc extension, and other supporting files. Understanding the basic syntax and structure is essential for addressing denials properly.
159
+ </p>
160
+
161
+ <p>
162
+ The fundamental building blocks of SELinux policy are types, attributes, classes, and permissions. Types label subjects like processes and objects like files. Attributes group types together. Classes define categories of objects like files, sockets, or processes. Permissions define what operations can be performed.
163
+ </p>
164
+
165
+ <p>
166
+ Policies are written as allow rules that grant specific permissions. The basic syntax follows this pattern.
167
+ </p>
168
+
169
+ ```te
170
+ allow source_type target_type:class { permissions };
171
+ ```
172
+
173
+ <p>
174
+ Let us work through a realistic example. Suppose you are developing a custom camera HAL and encounter this denial.
175
+ </p>
176
+
177
+ ```bash
178
+ avc: denied { open read write } for pid=2341 comm="camera.provider"
179
+ path="/dev/video0" dev="tmpfs" ino=1234
180
+ scontext=u:r:hal_camera_default:s0
181
+ tcontext=u:object_r:video_device:s0
182
+ tclass=chr_file permissive=0
183
+ ```
184
+
185
+ <p>
186
+ This denial tells us that the camera HAL process running in the hal_camera_default domain needs to open, read, and write to a video device. The proper way to address this is to add a policy rule allowing this specific access.
187
+ </p>
188
+
189
+ <p>
190
+ First, ensure the device file is properly labeled. In your device's file_contexts file, add or verify the label.
191
+ </p>
192
+
193
+ ```te
194
+ /dev/video[0-9]* u:object_r:video_device:s0
195
+ ```
196
+
197
+ <p>
198
+ Then, in your hal_camera_default.te policy file, add the allow rule.
199
+ </p>
200
+
201
+ ```te
202
+ allow hal_camera_default video_device:chr_file { open read write ioctl };
203
+ ```
204
+
205
+ <p>
206
+ Notice that we added ioctl permission as well. Camera devices typically require ioctl calls for configuration, so including this preemptively prevents future denials. However, we did not add excessive permissions like execute or append that are not needed.
207
+ </p>
208
+
209
+ <h2>Common Scenarios and Solutions</h2>
210
+
211
+ <p>
212
+ When developing a native service that needs to communicate over a socket, you will encounter denials related to socket operations. Here is how to properly handle a Unix domain socket scenario.
213
+ </p>
214
+
215
+ <p>
216
+ Suppose you have a custom service called myservice that needs to create a Unix socket for IPC. You would first define the domain and type.
217
+ </p>
218
+
219
+ ```te
220
+ # Define the domain for the service
221
+ type myservice, domain;
222
+ type myservice_exec, exec_type, file_type;
223
+
224
+ # Define the socket type
225
+ type myservice_socket, file_type;
226
+
227
+ # Allow the init process to transition to myservice domain
228
+ init_daemon_domain(myservice)
229
+
230
+ # Allow creating and using the socket
231
+ allow myservice myservice_socket:sock_file { create setattr unlink write };
232
+ allow myservice myservice_socket:dir { add_name write };
233
+
234
+ # Allow binding to the socket
235
+ allow myservice myservice_socket:unix_stream_socket { bind create listen };
236
+
237
+ # Allow clients to connect
238
+ allow untrusted_app myservice_socket:sock_file write;
239
+ allow untrusted_app myservice:unix_stream_socket connectto;
240
+ ```
241
+
242
+ <p>
243
+ For file access scenarios, be specific about what files are accessed. Avoid using broad types like system_file or vendor_file when you can define specific types for your resources.
244
+ </p>
245
+
246
+ ```te
247
+ # Define a specific type for your config files
248
+ type myservice_config_file, file_type;
249
+
250
+ # Label the files in file_contexts
251
+ /vendor/etc/myservice(/.*)? u:object_r:myservice_config_file:s0
252
+
253
+ # Grant read access to the config files
254
+ allow myservice myservice_config_file:dir r_dir_perms;
255
+ allow myservice myservice_config_file:file r_file_perms;
256
+ ```
257
+
258
+ <p>
259
+ The macros r_dir_perms and r_file_perms are predefined in Android's policy to grant standard read permissions. Using these macros makes policies more readable and consistent.
260
+ </p>
261
+
262
+ <h2>System Properties and SELinux</h2>
263
+
264
+ <p>
265
+ Android system properties have their own SELinux types and require special handling. Each property should have a specific type, and only authorized domains should be able to set or read it.
266
+ </p>
267
+
268
+ <p>
269
+ Define property types in property_contexts file.
270
+ </p>
271
+
272
+ ```te
273
+ vendor.myservice.enabled u:object_r:myservice_prop:s0
274
+ vendor.myservice.config u:object_r:myservice_prop:s0
275
+ ```
276
+
277
+ <p>
278
+ Then define the type and grant permissions in your te file.
279
+ </p>
280
+
281
+ ```te
282
+ # Define the property type
283
+ type myservice_prop, property_type;
284
+
285
+ # Allow the service to set its properties
286
+ set_prop(myservice, myservice_prop)
287
+
288
+ # Allow reading the property (if needed by other domains)
289
+ get_prop(system_server, myservice_prop)
290
+ ```
291
+
292
+ <p>
293
+ The set_prop and get_prop macros handle the underlying permissions needed for property operations. Never grant blanket access to default_prop or system_prop unless absolutely necessary and justified.
294
+ </p>
295
+
296
+ <h2>Vendor and Device Specific Policies</h2>
297
+
298
+ <p>
299
+ When working on device specific or vendor specific components, you should place policies in the appropriate directories. AOSP has a clear separation between system policies and vendor policies to maintain upgradeability.
300
+ </p>
301
+
302
+ <p>
303
+ System policies go in system/sepolicy and should only cover AOSP components. Vendor policies go in device/manufacturer/model/sepolicy or vendor/manufacturer/model/sepolicy depending on your tree structure. This separation ensures that system updates do not conflict with vendor customizations.
304
+ </p>
305
+
306
+ <p>
307
+ Project Treble introduced the concept of policy versioning. Vendor code must use only the public policy types and attributes exported by the system. Private types are not accessible across the boundary. This is enforced by neverallow rules.
308
+ </p>
309
+
310
+ ```te
311
+ # In vendor policy, use only public types
312
+ # This is correct
313
+ allow hal_vendor_myhal vendor_myhal_device:chr_file rw_file_perms;
314
+
315
+ # This would violate Treble requirements
316
+ # allow hal_vendor_myhal system_private_type:file read;
317
+ ```
318
+
319
+ <p>
320
+ When extending policies for proprietary components, create a clear naming scheme that identifies the vendor and purpose. Prefix types with vendor_ or the manufacturer name to avoid conflicts.
321
+ </p>
322
+
323
+ <h2>Debugging and Testing Policies</h2>
324
+
325
+ <p>
326
+ Testing SELinux policies requires methodical iteration. Start with the component in permissive mode, exercise all its functionality thoroughly, collect all denials, analyze them, write policies, and then test in enforcing mode.
327
+ </p>
328
+
329
+ <p>
330
+ Use the audit2allow tool to generate initial policy suggestions from denials, but always review and refine the output. The tool can suggest overly broad permissions.
331
+ </p>
332
+
333
+ ```bash
334
+ adb shell dmesg | grep avc | audit2allow
335
+ ```
336
+
337
+ <p>
338
+ The audit2allow output provides a starting point but should not be used verbatim. Review each suggested rule and narrow it down to the minimum necessary permissions. Consider whether the denial indicates a bug in your code rather than a missing policy.
339
+ </p>
340
+
341
+ <p>
342
+ When testing, verify that denials are actually resolved and that functionality works correctly. Simply making denials disappear is not enough. Ensure that your component operates as intended with the policies in place. Test error cases too, not just the happy path.
343
+ </p>
344
+
345
+ <p>
346
+ Use CTS and VTS tests to validate that your policies meet Android compatibility requirements. These tests include checks for policy correctness and security best practices. Failing these tests means your device cannot be certified.
347
+ </p>
348
+
349
+ <h2>Best Practices and Guidelines</h2>
350
+
351
+ <p>
352
+ Always follow the principle of least privilege. Grant only the minimum permissions necessary for functionality. If you are unsure whether a permission is needed, test without it first. It is easier to add permissions than to remove them after discovering they create security holes.
353
+ </p>
354
+
355
+ <p>
356
+ Document your policies with comments explaining why each rule exists. SELinux policy files can become complex, and future maintainers need to understand the reasoning behind decisions. Comments should explain what functionality the policy enables and why the permissions are necessary.
357
+ </p>
358
+
359
+ ```te
360
+ # The camera HAL needs to access video devices to capture images
361
+ # and videos. This includes opening the device, reading frame data,
362
+ # writing configuration via ioctl, and memory mapping buffers.
363
+ allow hal_camera_default video_device:chr_file { open read write ioctl map };
364
+ ```
365
+
366
+ <p>
367
+ Never use permissive domains in production builds. If you use permissive temporarily during development, add build system checks to ensure it is removed before release builds. Automated builds should fail if permissive domains are detected in production configurations.
368
+ </p>
369
+
370
+ <p>
371
+ Review neverallow rules in AOSP policy to understand what is explicitly forbidden. These rules exist to prevent common security mistakes. If your policy violates a neverallow rule, the build will fail. This is intentional and indicates you are trying to do something that breaks Android's security model.
372
+ </p>
373
+
374
+ <p>
375
+ Keep policies modular and organized. Group related rules together, use meaningful type names, and maintain a clear file structure. This makes policies easier to understand, review, and maintain over time.
376
+ </p>
377
+
378
+ <h2>Advanced Topics</h2>
379
+
380
+ <p>
381
+ Multi Level Security and Multi Category Security features of SELinux are used in Android to isolate apps from each other. Each app gets a unique category, ensuring that even if two apps run in the same domain, they cannot access each other's private data.
382
+ </p>
383
+
384
+ <p>
385
+ Type transitions define how security contexts change during certain operations. For example, when init starts a service, the process transitions from the init domain to the service specific domain. Understanding transitions is important for ensuring processes run in the correct context.
386
+ </p>
387
+
388
+ ```te
389
+ # When init executes myservice_exec, transition to myservice domain
390
+ domain_auto_trans(init, myservice_exec, myservice)
391
+ ```
392
+
393
+ <p>
394
+ Conditional policies allow rules to be enabled or disabled based on boolean values that can be changed at runtime. However, Android generally avoids conditional policies in favor of compile time policy decisions for better performance and security guarantees.
395
+ </p>
396
+
397
+ <p>
398
+ Understanding the SELinux policy compilation process helps debug complex issues. Policies are compiled into a binary format and loaded into the kernel at boot. Tools like sesearch and seinfo can query the compiled policy to verify what rules are actually in effect.
399
+ </p>
400
+
401
+ <h2>Conclusion</h2>
402
+
403
+ <p>
404
+ SELinux is a critical component of Android security that cannot be ignored or worked around through permissive mode. Properly addressing SELinux denials requires understanding the underlying security model, carefully analyzing what access is truly needed, and writing precise policies that grant minimum necessary permissions.
405
+ </p>
406
+
407
+ <p>
408
+ For developers working on AOSP or proprietary Android systems, investing time to learn SELinux pays dividends in system security and stability. Well crafted policies protect users from exploits, meet compliance requirements, and serve as documentation of security boundaries in the system architecture.
409
+ </p>
410
+
411
+ <p>
412
+ The key to success with SELinux is to treat it as an integral part of development from the start, not as an obstacle to be overcome at the end. Develop policies alongside code, test thoroughly, document decisions, and follow security best practices. The result will be a more secure, more maintainable Android system.
413
+ </p>
414
+
415
+ <p>
416
+ As Android continues to evolve, SELinux policies will become even more important. Newer Android versions tighten security requirements and expand the use of SELinux to cover more components. Developers who master SELinux policy development position themselves to build secure, compliant Android systems that protect user data and resist increasingly sophisticated attacks.
417
+ </p>
418
+
419
+ ---
420
+
421
+ <p style="font-size:10px;">
422
+ This article is a mirror of the original post written in Indonesian last year. Original post can be found at
423
+ <a href="https://hadadrjt.blogspot.com/2025/01/mengenal-memahami-dan-menganalisa.html" target="_blank">
424
+ https://hadadrjt.blogspot.com/2025/01/mengenal-memahami-dan-menganalisa.html
425
+ </a>
426
+ </p>
post/cicada 3301.md ADDED
@@ -0,0 +1,386 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ title: "Unveiling the Mystery of Cicada 3301: Puzzles, Conspiracies, and the Search for Identity"
3
+ date: 2025-08-19
4
+ description: In January 2012, an enigmatic image appeared on the internet forum 4chan that would spawn one of the most elaborate and mysterious puzzle hunts in digital history. The message was simple yet cryptic, stating that they were looking for highly intelligent individuals and inviting people to find a hidden message in the accompanying image. This marked the beginning of Cicada 3301, a phenomenon that has captivated cryptographers, hackers, linguists, and puzzle enthusiasts worldwide for over a decade.
5
+ author: Hadad Darajat
6
+ tags:
7
+ - cicada
8
+ - cicada_3301
9
+ ---
10
+
11
+ <p>
12
+ In January 2012, an enigmatic image appeared on the internet forum 4chan that would spawn one of the most elaborate and mysterious puzzle hunts in digital history. The message was simple yet cryptic, stating that they were looking for highly intelligent individuals and inviting people to find a hidden message in the accompanying image. This marked the beginning of Cicada 3301, a phenomenon that has captivated cryptographers, hackers, linguists, and puzzle enthusiasts worldwide for over a decade.
13
+ </p>
14
+
15
+ <p>
16
+ What started as a seemingly ordinary internet puzzle quickly evolved into a complex, multilayered challenge that spanned the digital and physical worlds. Cicada 3301 incorporated advanced cryptography, steganography, ancient texts, esoteric philosophy, and real world clues hidden in multiple countries. To this day, the true identity and purpose of Cicada 3301 remains one of the internet's greatest unsolved mysteries.
17
+ </p>
18
+
19
+ <h2>The First Emergence in 2012</h2>
20
+
21
+ <p>
22
+ On January 4, 2012, an anonymous user posted an image on 4chan's random board with the following text: "Hello. We are looking for highly intelligent individuals. To find them, we have devised a test. There is a message hidden in this image. Find it, and it will lead you on the road to finding us. We look forward to meeting the few that will make it all the way through. Good luck."
23
+ </p>
24
+
25
+ <p>
26
+ The image appeared to be a simple drawing of a cicada, but embedded within it was the first of many challenges. Using basic steganography techniques, solvers discovered that the image contained hidden data. By opening the image in a text editor or using steganography tools like OutGuess, they found a cipher that led to the next clue.
27
+ </p>
28
+
29
+ <p>
30
+ What made this puzzle extraordinary was its scope and sophistication. The initial image was just the beginning of a labyrinthine journey that would require knowledge of cryptography, programming, classical literature, occult symbolism, and even the ability to travel to physical locations around the world. The puzzle incorporated multiple encryption methods including Caesar ciphers, book codes, XOR ciphers, and more advanced techniques.
31
+ </p>
32
+
33
+ <p>
34
+ Early solvers found themselves decoding messages that referenced the Mabinogion, a collection of Welsh medieval tales, William Gibson's cyberpunk novel Agrippa, and various other literary and philosophical works. Clues led to websites on Tor hidden services, requiring participants to navigate the dark web. Some clues were physically posted in locations across multiple countries including the United States, Poland, France, South Korea, and Australia.
35
+ </p>
36
+
37
+ <p>
38
+ After approximately one month of intense collaboration and problem solving by the global community, Cicada 3301 announced that they had found the individuals they were looking for and thanked everyone who participated. The puzzle ended as mysteriously as it began, leaving most participants without answers about who Cicada was or what purpose the recruitment served.
39
+ </p>
40
+
41
+ <h2>The Return in 2013 and 2014</h2>
42
+
43
+ <p>
44
+ Exactly one year later, on January 4, 2013, Cicada 3301 returned with a new puzzle. This iteration was even more complex than the first, incorporating additional layers of cryptographic challenges and philosophical themes. The 2013 puzzle emphasized concepts of privacy, security, and the importance of protecting information in the digital age.
45
+ </p>
46
+
47
+ <p>
48
+ This second puzzle introduced a book called Liber Primus, a 60 page document written entirely in runes using a previously unknown runic alphabet. The book contained philosophical and spiritual passages, but large portions of it remained encrypted and unsolved to this day. The text that has been decoded discusses concepts of knowledge, enlightenment, and the nature of reality.
49
+ </p>
50
+
51
+ <p>
52
+ The 2013 puzzle also involved physical posters with QR codes appearing in multiple cities worldwide. These posters directed solvers to new websites and challenges, blending the digital treasure hunt with real world exploration. The complexity and global scale of the operation suggested significant resources and careful planning by the organizers.
53
+ </p>
54
+
55
+ <p>
56
+ A third puzzle appeared on January 4, 2014, following the same pattern of annual releases. However, this puzzle was shorter lived and ended with a message claiming that the entire event had been compromised by someone sharing answers and solutions prematurely, violating the spirit of individual problem solving that Cicada valued.
57
+ </p>
58
+
59
+ <p>
60
+ After 2014, no verified new puzzles from Cicada 3301 have appeared, despite numerous fake attempts by imposters. The sudden silence has only deepened the mystery and fueled speculation about what happened to the organization and whether they achieved whatever goal they were pursuing.
61
+ </p>
62
+
63
+ <h2>The Technical Complexity of the Puzzles</h2>
64
+
65
+ <p>
66
+ The Cicada 3301 puzzles were remarkable for their technical sophistication and diversity of challenges. Solving them required a broad range of skills that few individuals possessed alone, necessitating collaboration among communities of specialists.
67
+ </p>
68
+
69
+ <p>
70
+ Steganography was used extensively throughout the puzzles. The initial image in each year's puzzle contained hidden data that could be extracted using tools like OutGuess or by manually analyzing the image file structure. This technique hides information within seemingly innocent files without obviously altering their appearance.
71
+ </p>
72
+
73
+ ```bash
74
+ outguess -r cicada_image.jpg hidden_message.txt
75
+ ```
76
+
77
+ <p>
78
+ Cryptographic techniques ranged from classical ciphers to modern encryption. Solvers encountered Caesar ciphers, where letters are shifted by a fixed number, Vigenère ciphers using keyword based substitution, and book codes where numbers reference specific words in a text. More advanced challenges used XOR encryption, RSA cryptography, and custom designed cipher systems.
79
+ </p>
80
+
81
+ <p>
82
+ A book code example from the puzzles referenced specific editions of texts. Solvers needed to locate the exact edition specified, then use number sequences to extract words or letters. This required both cryptographic knowledge and literary detective work.
83
+ </p>
84
+
85
+ ```
86
+ Example book code format:
87
+ Page:Line:Word
88
+ Example: 15:7:3 might mean page 15, line 7, word 3
89
+ ```
90
+
91
+ <p>
92
+ The runes in Liber Primus represented an entirely new challenge. The Cicada runic alphabet, based on Anglo Saxon runes but with modifications, required solvers to first decode the alphabet itself before they could read the text. Portions of the text used additional encryption layers even after transliteration from runes to Latin characters.
93
+ </p>
94
+
95
+ <p>
96
+ The puzzle also incorporated number theory and mathematical concepts. Prime numbers featured prominently, which is fitting given that cicadas in nature are known for their prime numbered life cycles. Solvers needed to understand modular arithmetic, number bases, and other mathematical principles to progress.
97
+ </p>
98
+
99
+ <p>
100
+ Digital signatures using PGP encryption verified the authenticity of Cicada messages. This prevented imposters from creating fake puzzles and ensured that solvers could trust they were following legitimate clues. The use of cryptographic signatures demonstrated sophisticated operational security.
101
+ </p>
102
+
103
+ ```
104
+ Cicada 3301 PGP Signature:
105
+ -----BEGIN PGP SIGNED MESSAGE-----
106
+ Hash: SHA1
107
+
108
+ [Authentic Cicada Message]
109
+
110
+ -----BEGIN PGP SIGNATURE-----
111
+ [Signature block]
112
+ -----END PGP SIGNATURE-----
113
+ ```
114
+
115
+ <h2>Theories and Conspiracies</h2>
116
+
117
+ <p>
118
+ The mystery surrounding Cicada 3301's identity and purpose has generated numerous theories ranging from plausible to wildly speculative. Without official confirmation of who created the puzzles or why, the internet community has filled the void with conjecture.
119
+ </p>
120
+
121
+ <p>
122
+ One prominent theory suggests that Cicada 3301 was a recruitment tool for intelligence agencies such as the NSA, CIA, or GCHQ. The puzzles certainly tested skills valuable to signals intelligence work including cryptanalysis, linguistic ability, pattern recognition, and persistence. The global scope and sophisticated execution suggested organizational resources beyond what typical individuals or small groups could muster.
123
+ </p>
124
+
125
+ <p>
126
+ However, the emphasis on privacy, cryptography, and references to cypherpunk ideology seems inconsistent with government intelligence recruitment. Cicada's messages advocated for individual privacy and security, values often at odds with mass surveillance programs operated by intelligence agencies.
127
+ </p>
128
+
129
+ <p>
130
+ Another theory proposes that Cicada was created by a secret society or esoteric organization seeking to recruit members who demonstrated both intellectual capability and dedication. The philosophical content in Liber Primus, references to Gnosticism, mysticism, and enlightenment, and the emphasis on individual journey support this interpretation.
131
+ </p>
132
+
133
+ <p>
134
+ Some speculate that Cicada 3301 was a sophisticated alternate reality game or art project designed to explore themes of knowledge, secrecy, and human potential. The puzzles as performance art, creating meaning through the collective experience of solving them rather than serving an external recruitment purpose.
135
+ </p>
136
+
137
+ <p>
138
+ More conspiratorial theories link Cicada to groups like Anonymous, WikiLeaks, or other hacktivist organizations. The timing of the puzzles during periods of heightened awareness about digital privacy, following events like WikiLeaks releases and growing concerns about government surveillance, lends some credence to this idea.
139
+ </p>
140
+
141
+ <p>
142
+ A darker theory suggests Cicada could be connected to more nefarious purposes, though evidence for this is lacking. The secrecy and requirement that winners maintain silence about what happens after solving the puzzle has fueled speculation, but those who claim to have been contacted by Cicada describe philosophical discussions rather than illegal activities.
143
+ </p>
144
+
145
+ <p>
146
+ The most mundane explanation is that Cicada was created by a group of puzzle enthusiasts who wanted to challenge the internet's best minds and see how far they could push a collaborative problem solving community. The elaborate nature could simply reflect passion and dedication rather than serving an ulterior motive.
147
+ </p>
148
+
149
+ <h2>The Philosophy and Deeper Meaning</h2>
150
+
151
+ <p>
152
+ Beyond the technical challenges, Cicada 3301 incorporated significant philosophical and spiritual themes that suggested the puzzles were about more than just finding clever people. The decoded portions of Liber Primus and messages throughout the puzzles referenced concepts of enlightenment, the nature of reality, and the journey of self discovery.
153
+ </p>
154
+
155
+ <p>
156
+ The choice of the cicada as a symbol carries multiple meanings. In nature, cicadas spend years underground in darkness before emerging into light, a metaphor for transformation and enlightenment. Some species have 13 or 17 year life cycles, prime numbers that protect them from predators with shorter cycles. This mathematical elegance mirrors the mathematical elements in the puzzles.
157
+ </p>
158
+
159
+ <p>
160
+ Liber Primus contains passages that discuss the concept of knowledge as a form of liberation. The text emphasizes individual responsibility for seeking truth and warns against accepting received wisdom without personal verification. This aligns with Gnostic philosophy, which emphasizes direct personal experience of the divine over institutionalized religion.
161
+ </p>
162
+
163
+ <p>
164
+ The puzzles themselves embodied a philosophy of learning through doing. Participants could not passively receive answers but had to actively engage with challenges, learn new skills, and push beyond their comfort zones. The journey of solving the puzzle became a transformative experience for many participants.
165
+ </p>
166
+
167
+ <p>
168
+ References throughout the puzzles to privacy, cryptography, and individual sovereignty reflect cypherpunk ideology. The cypherpunk movement advocates for the use of cryptography and privacy enhancing technologies to bring about social and political change. By requiring use of Tor, PGP, and other privacy tools, Cicada educated participants about protecting themselves in the digital age.
169
+ </p>
170
+
171
+ <p>
172
+ The emphasis on collaboration despite being framed as a test for individuals highlighted the paradox of individual achievement versus collective knowledge. No single person possessed all the skills needed to solve the complete puzzle. Communities formed where cryptographers, linguists, programmers, and researchers shared knowledge and worked together, demonstrating that true intelligence includes knowing when to seek help.
173
+ </p>
174
+
175
+ <h2>The Community and Collaborative Solving</h2>
176
+
177
+ <p>
178
+ One of the most remarkable aspects of Cicada 3301 was the global community that formed to tackle the puzzles. Within hours of each puzzle's release, dedicated forums, IRC channels, and subreddits sprang up where thousands of people collaborated.
179
+ </p>
180
+
181
+ <p>
182
+ The community self organized remarkably efficiently. Specialists in different fields contributed their expertise. Cryptographers attacked ciphers, programmers wrote tools to automate analysis, linguists translated obscure texts, and researchers tracked down references to historical and philosophical works. People shared discoveries openly, building on each other's work.
183
+ </p>
184
+
185
+ <p>
186
+ Reddit's r/cicada and dedicated websites became central hubs for coordination. Solvers maintained wikis documenting every clue, solution, and dead end. The collaborative documentation ensured that knowledge was preserved and new participants could catch up without retracing every step.
187
+ </p>
188
+
189
+ <p>
190
+ Despite collaboration being essential, tension existed around the competitive aspect. Cicada stated they were looking for individuals, suggesting that only those who solved puzzles themselves would be selected. This created uncertainty about how much help was appropriate versus undermining the selection process.
191
+ </p>
192
+
193
+ <p>
194
+ The community also had to combat disinformation and red herrings. Trolls posted fake clues, imposters created false puzzles, and well intentioned but mistaken solvers sent others down wrong paths. Verifying information and maintaining focus on legitimate clues required discipline and critical thinking.
195
+ </p>
196
+
197
+ <p>
198
+ Interestingly, the Cicada community outlived the puzzles themselves. Even years after the last verified puzzle, communities continue discussing unsolved elements, particularly the undecrypted portions of Liber Primus. New generations of puzzle enthusiasts discover Cicada and attempt to crack what previous solvers could not.
199
+ </p>
200
+
201
+ <h2>Unsolved Mysteries and Remaining Questions</h2>
202
+
203
+ <p>
204
+ Despite the efforts of thousands of brilliant minds, significant aspects of Cicada 3301 remain mysterious and unsolved. These lingering questions continue to fascinate and frustrate the community.
205
+ </p>
206
+
207
+ <p>
208
+ The most prominent unsolved element is the majority of Liber Primus. Of the 60 pages, only a fraction has been successfully decrypted. The remaining pages resist all attempts at cryptanalysis. Solvers have tried every known cipher technique, looked for patterns, and applied computational power, yet the text keeps its secrets.
209
+ </p>
210
+
211
+ <p>
212
+ Some theorize that the undecrypted portions require information that was only given to those who completed the puzzle and were selected by Cicada. This would make public solution impossible, as the key was distributed privately. Others believe the cipher is solvable but requires an insight or approach that no one has yet discovered.
213
+ </p>
214
+
215
+ <p>
216
+ The identity of Cicada's creators remains completely unknown. Despite intensive investigation by journalists, security researchers, and internet sleuths, no credible evidence has emerged revealing who was behind the puzzles. The operational security was evidently excellent, with no leaks or mistakes that could compromise anonymity.
217
+ </p>
218
+
219
+ <p>
220
+ What happened to people who were recruited also remains unclear. A few individuals have claimed online that they were contacted after solving the puzzles, but their descriptions are vague and unverifiable. They describe being given additional challenges and philosophical discussions but claim to be bound by secrecy about specifics.
221
+ </p>
222
+
223
+ <p>
224
+ The purpose of the entire operation is still speculative. Did Cicada achieve its goal, whatever that was? Is that why the puzzles stopped after 2014? Or did something happen to prevent continuation? The lack of closure frustrates those who invested significant time and energy in solving the puzzles.
225
+ </p>
226
+
227
+ <p>
228
+ Whether Cicada 3301 will return remains an open question. Every January 4th, the community watches and waits, hoping for a new puzzle. So far, none have appeared, though fake attempts by imposters are common. Without the PGP signature, these are easily dismissed as fraudulent.
229
+ </p>
230
+
231
+ <h2>Technical Analysis of Specific Challenges</h2>
232
+
233
+ <p>
234
+ Examining specific challenges from the puzzles reveals the depth of knowledge required and the creativity of the puzzle designers. Each stage built on previous solutions and introduced new concepts.
235
+ </p>
236
+
237
+ <p>
238
+ The initial 2012 image steganography challenge used OutGuess, a program that hides data in JPEG images by modifying least significant bits in a way that resists statistical analysis. The hidden message was a cipher that required participants to recognize the encryption method and decrypt it.
239
+ </p>
240
+
241
+ <p>
242
+ One notable challenge involved a book code referencing the King James Bible and a specific edition of The Mabinogion. Solvers needed to identify which edition was referenced, obtain it, and use number sequences to extract letters that formed the next clue. The precision required demonstrated that random guessing would not work.
243
+ </p>
244
+
245
+ <p>
246
+ The use of Tor hidden services introduced many participants to the dark web for the first time. Clues provided .onion addresses that could only be accessed through Tor browser. This served both as a challenge and as education about anonymous communication technology.
247
+ </p>
248
+
249
+ <p>
250
+ Physical posters added a real world dimension. These posters appeared in over a dozen cities globally, suggesting either a distributed network of Cicada members or hired assistance in multiple countries. Each poster contained QR codes or other data that linked back to digital challenges.
251
+ </p>
252
+
253
+ <p>
254
+ The structure of many challenges followed a pattern. Initial analysis yielded a cipher or encoded message. Decryption revealed coordinates, URLs, or instructions leading to the next stage. This created a chain where each link depended on correctly solving the previous one, preventing shortcuts.
255
+ </p>
256
+
257
+ ```python
258
+ # Example of simple XOR decryption that appeared in puzzles
259
+ def xor_decrypt(ciphertext, key):
260
+ decrypted = []
261
+ for i in range(len(ciphertext)):
262
+ decrypted.append(chr(ord(ciphertext[i]) ^ ord(key[i % len(key)])))
263
+ return ''.join(decrypted)
264
+
265
+ # Solvers had to identify XOR was used and find the key
266
+ encrypted_msg = "encrypted_data_here"
267
+ key = "CICADA"
268
+ print(xor_decrypt(encrypted_msg, key))
269
+ ```
270
+
271
+ <h2>The Cultural Impact and Legacy</h2>
272
+
273
+ <p>
274
+ Cicada 3301 has left a lasting impact on internet culture and the puzzle solving community. It set a new standard for complexity and scope in alternate reality games and treasure hunts. Many subsequent puzzles and challenges explicitly reference Cicada or attempt to recreate its mystery.
275
+ </p>
276
+
277
+ <p>
278
+ The phenomenon has been featured in documentaries, news articles, podcasts, and even inspired fiction. Books and films have incorporated elements of Cicada, recognizing its place in internet mythology. The mystery resonates because it combines intellectual challenge with genuine unsolved questions.
279
+ </p>
280
+
281
+ <p>
282
+ Educational impact has been significant. Many people learned about cryptography, steganography, and information security through attempting Cicada puzzles. Universities have used Cicada as case studies in cybersecurity and cryptography courses, demonstrating practical applications of theoretical concepts.
283
+ </p>
284
+
285
+ <p>
286
+ The puzzles demonstrated the power of crowdsourced problem solving. Thousands of people worldwide collaborating in real time achieved what no individual could. This model of distributed intelligence has applications beyond puzzles, from scientific research to crisis response.
287
+ </p>
288
+
289
+ <p>
290
+ Cicada also raised awareness about privacy and surveillance issues. By requiring use of Tor and PGP, and through philosophical messages about privacy rights, the puzzles educated a generation about digital security during a period of growing concern about government and corporate surveillance.
291
+ </p>
292
+
293
+ <p>
294
+ The unsolved elements ensure Cicada's legacy continues. Each new generation of cryptographers and puzzle enthusiasts discovers the mystery and attempts to solve what others could not. The challenge of Liber Primus remains an open problem in cryptanalysis, potentially waiting for new techniques or insights.
295
+ </p>
296
+
297
+ <h2>Lessons and Reflections</h2>
298
+
299
+ <p>
300
+ Beyond the immediate experience of solving puzzles, Cicada 3301 offers broader lessons about knowledge, community, and the nature of mystery in the digital age.
301
+ </p>
302
+
303
+ <p>
304
+ The puzzles demonstrated that true intelligence is multifaceted. Success required not just technical skill but creativity, persistence, collaboration, and the wisdom to know one's limitations. The most brilliant cryptographer who refused to work with others would fail where a coordinated team succeeded.
305
+ </p>
306
+
307
+ <p>
308
+ Cicada highlighted the importance of operational security and anonymity. Despite intense scrutiny and investigation, the creators maintained complete anonymity. This demonstrates that with proper precautions, it is possible to operate anonymously even under significant attention, an important lesson for whistleblowers and activists.
309
+ </p>
310
+
311
+ <p>
312
+ The phenomenon shows how mystery and ambiguity can be more compelling than answers. If Cicada had been revealed as a mundane recruitment campaign or publicity stunt, interest would have evaporated. The continuing mystery sustains engagement and allows people to project their own meanings and interpretations.
313
+ </p>
314
+
315
+ <p>
316
+ The collaborative nature of solving highlighted both the best and worst of internet culture. At its best, people from diverse backgrounds and locations united to pursue knowledge and solve challenges. At its worst, competitive behavior, disinformation, and exclusionary attitudes emerged. The community had to actively work to maintain positive collaboration.
317
+ </p>
318
+
319
+ <p>
320
+ Cicada also demonstrated the hunger for intellectual challenge in modern society. Thousands of people devoted significant time and energy to solving puzzles with no promise of reward. The challenge itself was sufficient motivation. This suggests a widespread desire for meaningful mental engagement that much of modern life fails to provide.
321
+ </p>
322
+
323
+ <h2>The Search for Identity</h2>
324
+
325
+ <p>
326
+ Perhaps the most profound aspect of Cicada 3301 is how it served as a journey of self discovery for participants. Many who attempted the puzzles report that the experience changed them, teaching lessons that extended far beyond cryptography or puzzle solving.
327
+ </p>
328
+
329
+ <p>
330
+ Participants discovered capabilities they did not know they possessed. People who had never programmed before learned to code to create tools for analysis. Those unfamiliar with ancient texts delved into medieval literature. The challenges pushed people beyond their comfort zones and revealed hidden potential.
331
+ </p>
332
+
333
+ <p>
334
+ The experience also revealed limitations and the value of humility. Even the most skilled individuals encountered challenges beyond their expertise. Learning to ask for help, to admit ignorance, and to value others' contributions became necessary for progress. This built character alongside knowledge.
335
+ </p>
336
+
337
+ <p>
338
+ For many, engaging with Cicada's philosophical content prompted reflection on deeper questions. What is the nature of knowledge? What does it mean to be intelligent? What responsibilities come with capability? The puzzles raised questions that extended beyond the challenges themselves into how one should live.
339
+ </p>
340
+
341
+ <p>
342
+ The community aspect provided a sense of belonging and shared purpose. Participants found others who valued intellectual pursuits and problem solving. Friendships formed across geographical and cultural boundaries, united by common interest and mutual respect for each other's abilities.
343
+ </p>
344
+
345
+ <p>
346
+ The search for Cicada's identity mirrored participants' searches for their own identities. Who are we? What are we capable of? What communities do we belong to? What causes are worth pursuing? These questions emerged naturally from engagement with the puzzles.
347
+ </p>
348
+
349
+ <h2>Conclusion</h2>
350
+
351
+ <p>
352
+ Cicada 3301 remains one of the internet's most fascinating mysteries over a decade after its first appearance. The sophisticated puzzles, global scope, and continuing anonymity of the creators combine to create a phenomenon that captures imagination and resists easy explanation.
353
+ </p>
354
+
355
+ <p>
356
+ Whether Cicada was a recruitment tool, philosophical project, art installation, or something else entirely may never be definitively known. Perhaps the ambiguity is intentional, allowing the puzzles to mean different things to different people. The journey of attempting to solve them has value regardless of the destination.
357
+ </p>
358
+
359
+ <p>
360
+ The technical challenges pushed the boundaries of what was thought possible in collaborative problem solving. The philosophical content encouraged reflection on knowledge, privacy, and individual potential. The community that formed demonstrated both the possibilities and challenges of global collaboration.
361
+ </p>
362
+
363
+ <p>
364
+ For those who participated, Cicada was transformative. Skills were learned, friendships formed, and horizons expanded. The experience of pursuing something mysterious and challenging left lasting impressions that influenced careers and life paths.
365
+ </p>
366
+
367
+ <p>
368
+ The legacy of Cicada 3301 extends beyond the specific puzzles to represent something larger about human curiosity and the pursuit of knowledge. In an age of instant information and easy answers, Cicada provided genuine mystery and difficult challenges. It reminded us that some questions resist simple solutions and that the search itself has value.
369
+ </p>
370
+
371
+ <p>
372
+ As we move further into the digital age, with increasing surveillance, decreasing privacy, and growing concerns about control of information, Cicada's emphasis on cryptography, anonymity, and individual empowerment feels more relevant than ever. Whether the creators return or the mystery remains forever unsolved, Cicada 3301 has earned its place in internet history.
373
+ </p>
374
+
375
+ <p>
376
+ The undecrypted pages of Liber Primus still wait, a challenge to future cryptographers. The identity of the creators remains hidden, perhaps forever. And every January, the community watches and wonders if this will be the year Cicada returns. Until then, the mystery endures, continuing to inspire, challenge, and transform those who dare to seek the truth hidden within.
377
+ </p>
378
+
379
+ ---
380
+
381
+ <p style="font-size:10px;">
382
+ This article is a mirror of the original post written in Indonesian last year. Original post can be found at
383
+ <a href="https://hadadrjt.blogspot.com/2024/08/mengungkap-misteri-cicada-3301-puzzles.html" target="_blank">
384
+ https://hadadrjt.blogspot.com/2024/08/mengungkap-misteri-cicada-3301-puzzles.html
385
+ </a>
386
+ </p>
post/hf.md ADDED
@@ -0,0 +1,869 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ title: "HuggingFace: The Essential Platform Driving Artificial Intelligence Progress"
3
+ date: 2026-01-11
4
+ description: In the rapidly evolving landscape of artificial intelligence and machine learning, few platforms have had as transformative an impact as HuggingFace.
5
+ author: Hadad Darajat
6
+ tags:
7
+ - huggingface
8
+ - hf
9
+ - llm
10
+ - ai
11
+ - ml
12
+ ---
13
+
14
+ <p>
15
+ In the rapidly evolving landscape of artificial intelligence and machine learning, few platforms have had as transformative an impact as <strong>HuggingFace</strong>. What began as a chatbot company in 2016 has evolved into the de facto hub for sharing, discovering, and deploying machine learning models. Today, HuggingFace stands as a critical infrastructure that democratizes access to cutting edge AI technology, enabling researchers, developers, and organizations worldwide to build upon the latest advances in the field.
16
+ </p>
17
+
18
+ <blockquote>
19
+ "HuggingFace has done for machine learning what GitHub did for code collaboration. It transformed AI from isolated research labs into a collaborative, open ecosystem where innovation can flourish."
20
+ </blockquote>
21
+
22
+ <h2>From Chatbot Startup to AI Infrastructure</h2>
23
+
24
+ <p>
25
+ HuggingFace was founded in 2016 by <em>Clément Delangue, Julien Chaumond, and Thomas Wolf</em> in New York City. Initially, the company focused on building a chatbot app for teenagers, attempting to create an AI friend that could engage in natural conversations. While the chatbot itself did not achieve massive success, the underlying technology they developed would prove far more valuable.
26
+ </p>
27
+
28
+ <p>
29
+ The team realized that the natural language processing models they were building for their chatbot had broader applications. More importantly, they recognized that the AI research community desperately needed better tools for sharing and implementing the latest models. Research papers described groundbreaking techniques, but reproducing results required significant engineering effort and expertise.
30
+ </p>
31
+
32
+ <p>
33
+ In 2018, HuggingFace pivoted from consumer chatbots to developer tools, releasing the first version of their <strong>Transformers library</strong>. This open source Python library provided easy to use implementations of state of the art natural language processing models. The timing was perfect, coinciding with the transformer architecture revolution that was reshaping AI research.
34
+ </p>
35
+
36
+ <p>
37
+ The library's initial focus on implementing BERT, Google's breakthrough language model, made cutting edge NLP accessible to anyone with basic Python knowledge. What previously required weeks of work could now be accomplished in minutes. The developer community embraced it enthusiastically, and HuggingFace's trajectory changed forever.
38
+ </p>
39
+
40
+ <h2>The Transformers Library: Democratizing State of the Art AI</h2>
41
+
42
+ <p>
43
+ The <strong>Transformers library</strong> is the cornerstone of HuggingFace's ecosystem. It provides a unified API for working with thousands of pre trained models across multiple modalities including text, images, audio, and video. The library's design philosophy centers on three core principles:
44
+ </p>
45
+
46
+ <ul>
47
+ <li><strong>Easy to use</strong> with simple, intuitive APIs that abstract complex implementation details</li>
48
+ <li><strong>Flexible and powerful</strong> allowing customization for research and production needs</li>
49
+ <li><strong>Framework agnostic</strong> supporting PyTorch, TensorFlow, and JAX interchangeably</li>
50
+ </ul>
51
+
52
+ <h3>The Power of Simplicity</h3>
53
+
54
+ <p>
55
+ One of HuggingFace's greatest achievements is making advanced AI accessible through remarkably simple code. Consider a basic sentiment analysis task that would have required hundreds of lines of code and deep expertise just a few years ago.
56
+ </p>
57
+
58
+ ```python
59
+ from transformers import pipeline
60
+
61
+ # Create a sentiment analysis pipeline
62
+ classifier = pipeline("sentiment-analysis")
63
+
64
+ # Analyze text sentiment
65
+ result = classifier("HuggingFace has revolutionized AI development!")
66
+
67
+ print(result)
68
+ # Output: [{'label': 'POSITIVE', 'score': 0.9998}
69
+ ```
70
+
71
+ <p>
72
+ This simplicity extends to more complex tasks. Loading a pre trained model, fine tuning it on custom data, and deploying it for inference can be accomplished with minimal code. The library handles downloading models, managing dependencies, and optimizing performance automatically.
73
+ </p>
74
+
75
+ <h3>Supporting the Entire ML Lifecycle</h3>
76
+
77
+ <p>
78
+ The Transformers library supports every stage of the machine learning workflow:
79
+ </p>
80
+
81
+ <ol>
82
+ <li><strong>Model Discovery</strong> browsing and selecting from thousands of pre trained models</li>
83
+ <li><strong>Quick Prototyping</strong> testing models with pipeline abstractions</li>
84
+ <li><strong>Fine Tuning</strong> adapting pre trained models to specific tasks and datasets</li>
85
+ <li><strong>Training from Scratch</strong> implementing custom architectures when needed</li>
86
+ <li><strong>Evaluation</strong> measuring performance with standardized metrics</li>
87
+ <li><strong>Deployment</strong> exporting models for production environments</li>
88
+ <li><strong>Optimization</strong> quantization, distillation, and other efficiency techniques</li>
89
+ </ol>
90
+
91
+ <p>
92
+ A more realistic example showing fine tuning a model for text classification demonstrates the workflow:
93
+ </p>
94
+
95
+ ```python
96
+ from transformers import AutoTokenizer, AutoModelForSequenceClassification
97
+ from transformers import Trainer, TrainingArguments
98
+ from datasets import load_dataset
99
+
100
+ # Load pre-trained model and tokenizer
101
+ model_name = "bert-base-uncased"
102
+ tokenizer = AutoTokenizer.from_pretrained(model_name)
103
+ model = AutoModelForSequenceClassification.from_pretrained(
104
+ model_name,
105
+ num_labels=2
106
+ )
107
+
108
+ # Load and prepare dataset
109
+ dataset = load_dataset("imdb")
110
+
111
+ def tokenize_function(examples):
112
+ return tokenizer(
113
+ examples["text"],
114
+ padding="max_length",
115
+ truncation=True
116
+ )
117
+
118
+ tokenized_datasets = dataset.map(tokenize_function, batched=True)
119
+
120
+ # Define training parameters
121
+ training_args = TrainingArguments(
122
+ output_dir="./results",
123
+ num_train_epochs=3,
124
+ per_device_train_batch_size=16,
125
+ per_device_eval_batch_size=64,
126
+ warmup_steps=500,
127
+ weight_decay=0.01,
128
+ logging_dir="./logs",
129
+ )
130
+
131
+ # Create trainer and fine-tune
132
+ trainer = Trainer(
133
+ model=model,
134
+ args=training_args,
135
+ train_dataset=tokenized_datasets["train"],
136
+ eval_dataset=tokenized_datasets["test"]
137
+ )
138
+
139
+ trainer.train()
140
+ ```
141
+
142
+ <p>
143
+ This code fine tunes a BERT model on the IMDB movie review dataset for sentiment analysis. The abstraction level is perfect, hiding unnecessary complexity while maintaining flexibility for customization.
144
+ </p>
145
+
146
+ <h2>The Model Hub: GitHub for Machine Learning</h2>
147
+
148
+ <p>
149
+ The <strong>HuggingFace Model Hub</strong> is perhaps the platform's most visible and impactful component. It hosts over 300,000 models as of 2024, ranging from small specialized models to massive foundation models with hundreds of billions of parameters.
150
+ </p>
151
+
152
+ <h3>A Collaborative Ecosystem</h3>
153
+
154
+ <p>
155
+ The Model Hub operates on principles similar to GitHub, fostering collaboration and iteration. Key features include:
156
+ </p>
157
+
158
+ <ul>
159
+ <li><strong>Version control</strong> tracking model changes over time with Git integration</li>
160
+ <li><strong>Model cards</strong> standardized documentation explaining capabilities and limitations</li>
161
+ <li><strong>Licensing information</strong> clear usage rights and restrictions</li>
162
+ <li><strong>Community engagement</strong> discussions, issues, and contributions</li>
163
+ <li><strong>Automatic inference API</strong> testing models directly in the browser</li>
164
+ <li><strong>Performance metrics</strong> benchmarks and evaluation results</li>
165
+ </ul>
166
+
167
+ <p>
168
+ Anyone can upload models to the hub, from individual researchers sharing experiments to major organizations releasing production models. This openness has created an unprecedented repository of AI capabilities.
169
+ </p>
170
+
171
+ <h3>Diversity of Models</h3>
172
+
173
+ <p>
174
+ The hub contains models for virtually every AI task imaginable:
175
+ </p>
176
+
177
+ <p>
178
+ <strong>Natural Language Processing</strong> remains the largest category with models for:
179
+ </p>
180
+
181
+ <ul>
182
+ <li>Text classification and sentiment analysis</li>
183
+ <li>Named entity recognition and information extraction</li>
184
+ <li>Question answering and reading comprehension</li>
185
+ <li>Text generation and creative writing</li>
186
+ <li>Translation across hundreds of language pairs</li>
187
+ <li>Summarization of documents and articles</li>
188
+ <li>Conversational AI and dialogue systems</li>
189
+ </ul>
190
+
191
+ <p>
192
+ <strong>Computer Vision</strong> models handle:
193
+ </p>
194
+
195
+ <ul>
196
+ <li>Image classification and object detection</li>
197
+ <li>Semantic segmentation and instance segmentation</li>
198
+ <li>Image generation and style transfer</li>
199
+ <li>Visual question answering</li>
200
+ <li>Video understanding and action recognition</li>
201
+ <li>Optical character recognition</li>
202
+ </ul>
203
+
204
+ <p>
205
+ <strong>Audio Processing</strong> capabilities include:
206
+ </p>
207
+
208
+ <ul>
209
+ <li>Automatic speech recognition</li>
210
+ <li>Text to speech synthesis</li>
211
+ <li>Audio classification and event detection</li>
212
+ <li>Music generation and audio enhancement</li>
213
+ <li>Speaker identification and diarization</li>
214
+ </ul>
215
+
216
+ <p>
217
+ <strong>Multimodal Models</strong> that combine different data types:
218
+ </p>
219
+
220
+ <ul>
221
+ <li>Vision language models like CLIP and BLIP</li>
222
+ <li>Image captioning and visual reasoning</li>
223
+ <li>Text to image generation like Stable Diffusion</li>
224
+ <li>Audio visual learning</li>
225
+ </ul>
226
+
227
+ <h3>Foundation Models and the Democratization of AI</h3>
228
+
229
+ <p>
230
+ The hub hosts many of the most important <em>foundation models</em> that have defined recent AI progress. Models like GPT-2, BLOOM, LLaMA, Stable Diffusion, and Whisper are freely available, allowing researchers and developers worldwide to build upon cutting edge technology.
231
+ </p>
232
+
233
+ <blockquote>
234
+ "Before HuggingFace, if you wanted to work with state of the art models, you either worked at a major tech company or spent months reimplementing research papers. Now, you can download a model that cost millions to train and start using it in minutes."
235
+ </blockquote>
236
+
237
+ <p>
238
+ This democratization has profound implications. Small startups can compete with tech giants by leveraging the same models. Researchers in developing countries can contribute to AI advancement without access to massive compute resources. Students can learn by experimenting with real production quality models rather than toy examples.
239
+ </p>
240
+
241
+ <h2>Datasets: The Fuel for Machine Learning</h2>
242
+
243
+ <p>
244
+ Recognizing that models are only as good as the data they train on, HuggingFace created the <strong>Datasets library</strong> and corresponding hub. This addresses a critical bottleneck in machine learning, data access and preprocessing.
245
+ </p>
246
+
247
+ <h3>Standardized Data Access</h3>
248
+
249
+ <p>
250
+ The Datasets library provides a unified interface for loading and processing datasets. It handles the messy details of downloading, caching, and formatting data from various sources.
251
+ </p>
252
+
253
+ ```python
254
+ from datasets import load_dataset
255
+
256
+ # Load a dataset with a single line
257
+ dataset = load_dataset("squad")
258
+
259
+ # Access training examples
260
+ print(dataset["train"][0])
261
+
262
+ # Common NLP datasets are readily available
263
+ imdb = load_dataset("imdb")
264
+ glue = load_dataset("glue", "mrpc")
265
+ common_voice = load_dataset("mozilla-foundation/common_voice_11_0", "en")
266
+
267
+ # Even massive datasets are handled efficiently
268
+ c4 = load_dataset("c4", "en", streaming=True)
269
+ ```
270
+
271
+ <p>
272
+ The library uses <strong>Apache Arrow</strong> under the hood, enabling efficient handling of datasets too large to fit in memory. The streaming mode allows working with terabyte scale datasets on consumer hardware.
273
+ </p>
274
+
275
+ <h3>Data Processing Made Easy</h3>
276
+
277
+ <p>
278
+ The Datasets library excels at data transformation and preprocessing:
279
+ </p>
280
+
281
+ ```python
282
+ from datasets import load_dataset
283
+
284
+ dataset = load_dataset("imdb")
285
+
286
+ # Map transformations across the dataset
287
+ def uppercase_text(example):
288
+ example["text"] = example["text"].upper()
289
+ return example
290
+
291
+ dataset = dataset.map(uppercase_text)
292
+
293
+ # Filter examples
294
+ positive_reviews = dataset.filter(lambda x: x["label"] == 1)
295
+
296
+ # Split and shuffle
297
+ dataset = dataset.train_test_split(test_size=0.2, shuffle=True)
298
+
299
+ # Select columns
300
+ dataset = dataset.remove_columns(["unused_column"])
301
+
302
+ # Combine datasets
303
+ combined = concatenate_datasets([dataset1, dataset2])
304
+ ```
305
+
306
+ <h3>The Dataset Hub</h3>
307
+
308
+ <p>
309
+ Similar to the Model Hub, HuggingFace hosts a <strong>Dataset Hub</strong> with over 50,000 datasets covering diverse domains and languages. This includes:
310
+ </p>
311
+
312
+ <ul>
313
+ <li><strong>Benchmark datasets</strong> for standardized evaluation like GLUE, SuperGLUE, SQuAD</li>
314
+ <li><strong>Domain specific data</strong> for medical, legal, scientific, and financial applications</li>
315
+ <li><strong>Multilingual corpora</strong> enabling AI for low resource languages</li>
316
+ <li><strong>Multimodal datasets</strong> pairing images with text, audio with transcripts</li>
317
+ <li><strong>Synthetic data</strong> generated for privacy preserving AI development</li>
318
+ </ul>
319
+
320
+ <p>
321
+ Users can upload private datasets for internal use or share publicly to advance research. The platform handles versioning, documentation, and licensing similar to models.
322
+ </p>
323
+
324
+ <h2>Spaces: Democratizing Model Deployment</h2>
325
+
326
+ <p>
327
+ <strong>HuggingFace Spaces</strong> addresses the final piece of the AI development puzzle, deployment and sharing. Spaces allows anyone to create and host machine learning applications with minimal infrastructure knowledge.
328
+ </p>
329
+
330
+ <h3>Multiple Frameworks Supported</h3>
331
+
332
+ <p>
333
+ Spaces supports popular Python frameworks for building AI applications:
334
+ </p>
335
+
336
+ <ul>
337
+ <li><strong>Gradio</strong> for quick interactive demos with minimal code</li>
338
+ <li><strong>Streamlit</strong> for data applications and dashboards</li>
339
+ <li><strong>Static HTML/JS</strong> for custom web applications</li>
340
+ <li><strong>Docker</strong> for complete control over the environment</li>
341
+ </ul>
342
+
343
+ <p>
344
+ A simple Gradio space might look like this:
345
+ </p>
346
+
347
+ ```python
348
+ import gradio as gr
349
+ from transformers import pipeline
350
+
351
+ # Load a model
352
+ classifier = pipeline("sentiment-analysis")
353
+
354
+ def analyze_sentiment(text):
355
+ result = classifier(text)[0]
356
+ return f"Sentiment: {result['label']}, Confidence: {result['score']:.2f}"
357
+
358
+ # Create interface
359
+ demo = gr.Interface(
360
+ fn=analyze_sentiment,
361
+ inputs=gr.Textbox(lines=5, placeholder="Enter text here..."),
362
+ outputs="text",
363
+ title="Sentiment Analysis",
364
+ description="Analyze the sentiment of any text"
365
+ )
366
+
367
+ # Launch the app
368
+ demo.launch()
369
+ ```
370
+
371
+ <p>
372
+ This code creates a fully functional web application for sentiment analysis that can be shared with anyone via a public URL. No server configuration, no deployment complexity, just write the code and HuggingFace handles the rest.
373
+ </p>
374
+
375
+ <h3>Community Showcases and Learning</h3>
376
+
377
+ <p>
378
+ Spaces has become a vibrant showcase of AI capabilities. Developers create demos of:
379
+ </p>
380
+
381
+ <ul>
382
+ <li><strong>Latest research</strong> making papers interactive and accessible</li>
383
+ <li><strong>Novel applications</strong> combining models in creative ways</li>
384
+ <li><strong>Educational tools</strong> helping others learn about AI</li>
385
+ <li><strong>Comparison platforms</strong> evaluating different models side by side</li>
386
+ <li><strong>Prototypes</strong> testing ideas before full development</li>
387
+ </ul>
388
+
389
+ <p>
390
+ The ease of creating Spaces has dramatically lowered the barrier for sharing AI work. Researchers can accompany papers with interactive demos. Educators can create hands on learning experiences. Enthusiasts can experiment and share discoveries.
391
+ </p>
392
+
393
+ <h2>The Business Model and Sustainability</h2>
394
+
395
+ <p>
396
+ HuggingFace has successfully built a sustainable business while maintaining its commitment to open source and community. The company offers several revenue streams:
397
+ </p>
398
+
399
+ <h3>Enterprise Solutions</h3>
400
+
401
+ <p>
402
+ <strong>HuggingFace Enterprise</strong> provides organizations with:
403
+ </p>
404
+
405
+ <ul>
406
+ <li>Private model and dataset hosting</li>
407
+ <li>Advanced security and compliance features</li>
408
+ <li>Dedicated support and consulting</li>
409
+ <li>Custom model training and deployment</li>
410
+ <li>Integration with enterprise infrastructure</li>
411
+ </ul>
412
+
413
+ <h3>Inference Endpoints</h3>
414
+
415
+ <p>
416
+ The <strong>Inference Endpoints</strong> service allows deploying models as scalable APIs without managing infrastructure. Users pay for compute time, and HuggingFace handles:
417
+ </p>
418
+
419
+ <ul>
420
+ <li>Auto scaling based on demand</li>
421
+ <li>Load balancing and redundancy</li>
422
+ <li>Model optimization and caching</li>
423
+ <li>Monitoring and logging</li>
424
+ <li>GPU and CPU deployment options</li>
425
+ </ul>
426
+
427
+ <h3>AutoTrain and Expert Acceleration Program</h3>
428
+
429
+ <p>
430
+ <strong>AutoTrain</strong> provides a no code solution for training custom models. Users upload data, select objectives, and AutoTrain handles the entire training process including:
431
+ </p>
432
+
433
+ <ol>
434
+ <li>Automatic model selection</li>
435
+ <li>Hyperparameter optimization</li>
436
+ <li>Training on cloud infrastructure</li>
437
+ <li>Model evaluation and comparison</li>
438
+ <li>Deployment to production</li>
439
+ </ol>
440
+
441
+ <p>
442
+ The <strong>Expert Acceleration Program</strong> connects organizations with HuggingFace engineers for custom projects, training, and implementation support.
443
+ </p>
444
+
445
+ <h3>Hardware Partnerships</h3>
446
+
447
+ <p>
448
+ HuggingFace partners with hardware manufacturers to optimize models for specific platforms. These partnerships provide revenue while ensuring the ecosystem works efficiently across different hardware configurations.
449
+ </p>
450
+
451
+ <p>
452
+ Importantly, the core platform remains <em>free and open source</em>. The business model does not rely on restricting access but on providing value added services for organizations with specific needs.
453
+ </p>
454
+
455
+ <h2>Impact on AI Research and Development</h2>
456
+
457
+ <p>
458
+ HuggingFace's influence on AI progress cannot be overstated. The platform has fundamentally changed how AI research is conducted and disseminated.
459
+ </p>
460
+
461
+ <h3>Accelerating Research Iteration</h3>
462
+
463
+ <p>
464
+ Before HuggingFace, reproducing research results was notoriously difficult. Papers described architectures and training procedures, but implementation details were often missing or unclear. Researchers spent weeks or months reimplementing work before they could build upon it.
465
+ </p>
466
+
467
+ <p>
468
+ Now, researchers upload models alongside papers. Others can immediately download, test, and extend the work. This has <strong>dramatically accelerated the pace of research</strong>. Ideas can be validated or refuted quickly. Comparisons between approaches are standardized and fair.
469
+ </p>
470
+
471
+ <blockquote>
472
+ "HuggingFace transformed AI from a field where replicating results was a major achievement to one where we can immediately build on each other's work. The compound effect on research velocity has been immense."
473
+ <br><em>- AI Researcher at a major university</em>
474
+ </blockquote>
475
+
476
+ <h3>Enabling Reproducibility and Transparency</h3>
477
+
478
+ <p>
479
+ The AI research community has struggled with reproducibility. Results claimed in papers sometimes could not be reproduced due to:
480
+ </p>
481
+
482
+ <ul>
483
+ <li>Missing implementation details</li>
484
+ <li>Undisclosed hyperparameters</li>
485
+ <li>Dataset preprocessing ambiguities</li>
486
+ <li>Random seed sensitivity</li>
487
+ <li>Hardware specific optimizations</li>
488
+ </ul>
489
+
490
+ <p>
491
+ HuggingFace addresses this by encouraging researchers to share complete artifacts. Model cards document training procedures, datasets, evaluation metrics, and known limitations. Version control tracks changes over time. The community can verify claims by running models themselves.
492
+ </p>
493
+
494
+ <h3>Democratizing Access to Cutting Edge AI</h3>
495
+
496
+ <p>
497
+ Perhaps HuggingFace's greatest contribution is making advanced AI accessible globally. In the past, working with state of the art models required:
498
+ </p>
499
+
500
+ <ul>
501
+ <li><strong>Massive compute resources</strong> for training from scratch</li>
502
+ <li><strong>Large teams</strong> with specialized expertise</li>
503
+ <li><strong>Significant funding</strong> for infrastructure and personnel</li>
504
+ <li><strong>Access to proprietary data</strong> collected at scale</li>
505
+ </ul>
506
+
507
+ <p>
508
+ Now, anyone with a laptop and internet connection can:
509
+ </p>
510
+
511
+ <ul>
512
+ <li>Download models trained on billions of parameters</li>
513
+ <li>Fine tune them for specific tasks with modest data</li>
514
+ <li>Deploy applications serving millions of users</li>
515
+ <li>Contribute to advancing the field</li>
516
+ </ul>
517
+
518
+ <p>
519
+ This democratization has profound geopolitical implications. AI capability is no longer concentrated in a few wealthy countries and corporations. Researchers in developing nations can contribute meaningfully. Small organizations can innovate without massive capital.
520
+ </p>
521
+
522
+ <h2>Case Studies and Real World Applications</h2>
523
+
524
+ <p>
525
+ HuggingFace powers AI applications across industries and use cases. Several examples illustrate the platform's versatility and impact.
526
+ </p>
527
+
528
+ <h3>Healthcare and Medical Research</h3>
529
+
530
+ <p>
531
+ Medical researchers use HuggingFace models for:
532
+ </p>
533
+
534
+ <ul>
535
+ <li><strong>Clinical note analysis</strong> extracting structured information from unstructured records</li>
536
+ <li><strong>Literature review</strong> summarizing thousands of research papers</li>
537
+ <li><strong>Diagnosis support</strong> analyzing symptoms and suggesting investigations</li>
538
+ <li><strong>Drug discovery</strong> predicting molecular properties and interactions</li>
539
+ <li><strong>Medical imaging</strong> detecting abnormalities in X-rays, MRIs, and CT scans</li>
540
+ </ul>
541
+
542
+ <p>
543
+ Models fine tuned on medical datasets achieve performance comparable to specialists in some narrow tasks, while being available 24/7 and scalable to serve underserved populations.
544
+ </p>
545
+
546
+ <h3>Content Creation and Media</h3>
547
+
548
+ <p>
549
+ Media organizations and creators leverage HuggingFace for:
550
+ </p>
551
+
552
+ <ul>
553
+ <li><strong>Automated transcription</strong> converting audio and video to text</li>
554
+ <li><strong>Content moderation</strong> detecting harmful or inappropriate material</li>
555
+ <li><strong>Recommendation systems</strong> suggesting relevant articles or products</li>
556
+ <li><strong>Image generation</strong> creating illustrations and visual content</li>
557
+ <li><strong>Translation</strong> making content accessible across languages</li>
558
+ </ul>
559
+
560
+ <h3>Customer Service and Support</h3>
561
+
562
+ <p>
563
+ Businesses deploy HuggingFace powered chatbots and assistants that:
564
+ </p>
565
+
566
+ <ul>
567
+ <li>Answer frequently asked questions automatically</li>
568
+ <li>Route complex queries to appropriate human agents</li>
569
+ <li>Analyze customer sentiment to prioritize urgent issues</li>
570
+ <li>Generate personalized responses based on customer history</li>
571
+ <li>Operate across multiple languages and time zones</li>
572
+ </ul>
573
+
574
+ <h3>Education and Accessibility</h3>
575
+
576
+ <p>
577
+ Educational applications include:
578
+ </p>
579
+
580
+ <ul>
581
+ <li><strong>Automated essay grading</strong> providing instant feedback to students</li>
582
+ <li><strong>Personalized tutoring</strong> adapting explanations to student level</li>
583
+ <li><strong>Accessibility tools</strong> converting text to speech for visually impaired users</li>
584
+ <li><strong>Language learning</strong> providing conversation practice and pronunciation feedback</li>
585
+ <li><strong>Content simplification</strong> making complex texts accessible to different reading levels</li>
586
+ </ul>
587
+
588
+ <h2>Community and Collaborative Culture</h2>
589
+
590
+ <p>
591
+ Beyond technology, HuggingFace has cultivated a <strong>vibrant community</strong> that embodies open source values and collaborative spirit.
592
+ </p>
593
+
594
+ <h3>Open Source Contribution</h3>
595
+
596
+ <p>
597
+ The Transformers library has over 2,000 contributors who have submitted improvements, bug fixes, and new features. This collaborative development model ensures:
598
+ </p>
599
+
600
+ <ul>
601
+ <li>Rapid iteration and improvement</li>
602
+ <li>Diverse perspectives and use cases considered</li>
603
+ <li>Community ownership and investment</li>
604
+ <li>Distributed expertise and knowledge sharing</li>
605
+ </ul>
606
+
607
+ <h3>Educational Resources and Documentation</h3>
608
+
609
+ <p>
610
+ HuggingFace invests heavily in education through:
611
+ </p>
612
+
613
+ <ul>
614
+ <li><strong>Comprehensive documentation</strong> with tutorials for every skill level</li>
615
+ <li><strong>Free courses</strong> teaching NLP, computer vision, and audio processing</li>
616
+ <li><strong>YouTube videos and webinars</strong> covering new features and techniques</li>
617
+ <li><strong>Community forums</strong> where users help each other</li>
618
+ <li><strong>Blog posts</strong> explaining research and announcing updates</li>
619
+ </ul>
620
+
621
+ <h3>Events and Competitions</h3>
622
+
623
+ <p>
624
+ The platform hosts regular events that bring the community together:
625
+ </p>
626
+
627
+ <ul>
628
+ <li><strong>Model training competitions</strong> with prizes and recognition</li>
629
+ <li><strong>Hackathons</strong> building applications around themes</li>
630
+ <li><strong>Paper implementation challenges</strong> reproducing recent research</li>
631
+ <li><strong>Community sprints</strong> collaborating on specific improvements</li>
632
+ </ul>
633
+
634
+ <p>
635
+ These events serve multiple purposes, advancing the state of the art, building skills, fostering connections, and identifying talent.
636
+ </p>
637
+
638
+ <h2>Challenges and Criticisms</h2>
639
+
640
+ <p>
641
+ Despite its success, HuggingFace faces challenges and legitimate criticisms that deserve consideration.
642
+ </p>
643
+
644
+ <h3>Environmental Concerns</h3>
645
+
646
+ <p>
647
+ Training large language models consumes <em>enormous amounts of energy</em> and produces significant carbon emissions. While HuggingFace promotes sharing pre trained models to reduce redundant training, the platform still facilitates carbon intensive AI development.
648
+ </p>
649
+
650
+ <p>
651
+ Critics argue that easier access to model training encourages unnecessary experimentation and waste. The company has responded by:
652
+ </p>
653
+
654
+ <ul>
655
+ <li>Partnering with carbon neutral compute providers</li>
656
+ <li>Providing carbon footprint estimates for training</li>
657
+ <li>Encouraging efficient models and techniques</li>
658
+ <li>Researching greener AI approaches</li>
659
+ </ul>
660
+
661
+ <h3>Model Safety and Misuse</h3>
662
+
663
+ <p>
664
+ Open access to powerful AI models raises safety concerns. Models can be misused for:
665
+ </p>
666
+
667
+ <ul>
668
+ <li>Generating misinformation and propaganda</li>
669
+ <li>Creating deepfakes and synthetic media</li>
670
+ <li>Bypassing security systems</li>
671
+ <li>Automating harassment or abuse</li>
672
+ <li>Enabling surveillance and privacy violations</li>
673
+ </ul>
674
+
675
+ <p>
676
+ HuggingFace attempts to balance openness with responsibility through:
677
+ </p>
678
+
679
+ <ul>
680
+ <li><strong>Model cards</strong> documenting limitations and ethical considerations</li>
681
+ <li><strong>Content policy</strong> prohibiting certain types of models</li>
682
+ <li><strong>Gating mechanisms</strong> requiring agreement to terms before access</li>
683
+ <li><strong>Reporting tools</strong> for flagging problematic content</li>
684
+ </ul>
685
+
686
+ <p>
687
+ However, the tension between open access and preventing harm remains an ongoing challenge without easy answers.
688
+ </p>
689
+
690
+ <h3>Bias and Fairness</h3>
691
+
692
+ <p>
693
+ Models hosted on HuggingFace can perpetuate and amplify biases present in training data. These biases affect:
694
+ </p>
695
+
696
+ <ul>
697
+ <li>Gender and racial stereotypes</li>
698
+ <li>Cultural and linguistic representation</li>
699
+ <li>Socioeconomic assumptions</li>
700
+ <li>Geographic and historical perspectives</li>
701
+ </ul>
702
+
703
+ <p>
704
+ The platform encourages transparency about biases through model cards and evaluation metrics, but ultimately, addressing bias requires improvements in datasets and training methodologies across the entire AI field.
705
+ </p>
706
+
707
+ <h3>Centralization Concerns</h3>
708
+
709
+ <p>
710
+ As HuggingFace becomes increasingly central to AI infrastructure, some worry about <em>over dependence</em> on a single platform. Potential risks include:
711
+ </p>
712
+
713
+ <ul>
714
+ <li>Platform downtime affecting many downstream applications</li>
715
+ <li>Policy changes impacting access or pricing</li>
716
+ <li>Acquisition by larger companies changing priorities</li>
717
+ <li>Government pressure to restrict access in certain regions</li>
718
+ </ul>
719
+
720
+ <p>
721
+ The open source nature of the core libraries mitigates some risks, as the code can be forked and self hosted if necessary. However, the community network effects and hosted infrastructure create lock in.
722
+ </p>
723
+
724
+ <h2>The Competitive Landscape</h2>
725
+
726
+ <p>
727
+ HuggingFace operates in an increasingly competitive space with several notable alternatives and complementary platforms.
728
+ </p>
729
+
730
+ <h3>GitHub and GitLab</h3>
731
+
732
+ <p>
733
+ While primarily for code, GitHub and GitLab increasingly host ML models and datasets. GitHub's LFS supports large files, and organizations use these platforms for versioning ML artifacts. However, they lack the ML specific features like model cards, inference APIs, and specialized search that HuggingFace provides.
734
+ </p>
735
+
736
+ <h3>AWS SageMaker, Google Vertex AI, Azure ML</h3>
737
+
738
+ <p>
739
+ Cloud providers offer comprehensive ML platforms with:
740
+ </p>
741
+
742
+ <ul>
743
+ <li>Managed training infrastructure</li>
744
+ <li>Model deployment and serving</li>
745
+ <li>Integration with cloud services</li>
746
+ <li>Enterprise security and compliance</li>
747
+ </ul>
748
+
749
+ <p>
750
+ These platforms target enterprises willing to pay for convenience and integration, while HuggingFace focuses on community and open access. There is actually significant collaboration, with HuggingFace integrating with all major cloud providers.
751
+ </p>
752
+
753
+ <h3>Weights and Biases, MLflow</h3>
754
+
755
+ <p>
756
+ Experiment tracking and model management tools like W&B and MLflow overlap with some HuggingFace functionality but focus on different aspects of the workflow. Many users combine these tools with HuggingFace.
757
+ </p>
758
+
759
+ <h3>Replicate, Banana, Modal</h3>
760
+
761
+ <p>
762
+ Newer platforms focus specifically on model deployment and inference, competing with HuggingFace's inference endpoints. They often emphasize developer experience and serverless architectures.
763
+ </p>
764
+
765
+ <p>
766
+ Despite competition, HuggingFace maintains advantages in:
767
+ </p>
768
+
769
+ <ul>
770
+ <li><strong>Community size and engagement</strong> creating network effects</li>
771
+ <li><strong>Model variety and quantity</strong> the largest repository</li>
772
+ <li><strong>Open source commitment</strong> building trust and contribution</li>
773
+ <li><strong>End to end coverage</strong> supporting the entire ML workflow</li>
774
+ </ul>
775
+
776
+ <h2>The Future of HuggingFace and AI Infrastructure</h2>
777
+
778
+ <p>
779
+ Looking forward, HuggingFace is positioned to play an increasingly important role in AI development. Several trends suggest the platform's continued growth and evolution.
780
+ </p>
781
+
782
+ <h3>Multimodal AI and Foundation Models</h3>
783
+
784
+ <p>
785
+ The shift toward <strong>multimodal models</strong> that process text, images, audio, and video simultaneously aligns with HuggingFace's unified approach. As foundation models become more capable and general purpose, the platform's role as a distribution and collaboration hub becomes more valuable.
786
+ </p>
787
+
788
+ <h3>Edge AI and Optimization</h3>
789
+
790
+ <p>
791
+ Deploying AI on edge devices like smartphones, IoT sensors, and embedded systems requires model optimization. HuggingFace is investing in:
792
+ </p>
793
+
794
+ <ul>
795
+ <li>Quantization techniques reducing model size</li>
796
+ <li>Knowledge distillation creating smaller models</li>
797
+ <li>Hardware specific optimization for mobile and edge</li>
798
+ <li>Tools for measuring and improving efficiency</li>
799
+ </ul>
800
+
801
+ <h3>Personalization and Privacy</h3>
802
+
803
+ <p>
804
+ Growing privacy concerns drive interest in <em>on device AI</em> and federated learning. HuggingFace could facilitate these approaches by:
805
+ </p>
806
+
807
+ <ul>
808
+ <li>Hosting models optimized for local deployment</li>
809
+ <li>Providing tools for federated fine tuning</li>
810
+ <li>Supporting differential privacy techniques</li>
811
+ <li>Enabling secure multi party computation</li>
812
+ </ul>
813
+
814
+ <h3>Governance and Standards</h3>
815
+
816
+ <p>
817
+ As AI regulation emerges globally, standardized approaches to model documentation, evaluation, and risk assessment become critical. HuggingFace's model cards and evaluation frameworks position the platform to help shape industry standards.
818
+ </p>
819
+
820
+ <h3>Expansion Beyond Language Models</h3>
821
+
822
+ <p>
823
+ While rooted in NLP, HuggingFace is expanding into:
824
+ </p>
825
+
826
+ <ul>
827
+ <li><strong>Robotics</strong> models for control and perception</li>
828
+ <li><strong>Scientific computing</strong> models for biology, chemistry, physics</li>
829
+ <li><strong>Finance</strong> models for trading, risk assessment, fraud detection</li>
830
+ <li><strong>Climate and sustainability</strong> models for environmental monitoring</li>
831
+ </ul>
832
+
833
+ <p>
834
+ This expansion makes HuggingFace increasingly central to AI across all domains.
835
+ </p>
836
+
837
+ <h2>Conclusion: The Infrastructure of AI's Future</h2>
838
+
839
+ <p>
840
+ HuggingFace has evolved from a chatbot startup into critical infrastructure for artificial intelligence development. The platform's success stems from understanding that AI progress requires not just algorithms but <strong>collaboration, accessibility, and community</strong>.
841
+ </p>
842
+
843
+ <p>
844
+ By making state of the art models freely available, providing intuitive tools, and fostering an open collaborative culture, HuggingFace has democratized AI in ways previously unimaginable. Researchers worldwide can access models that cost millions to train. Students can experiment with cutting edge technology. Small teams can build applications that compete with tech giants.
845
+ </p>
846
+
847
+ <blockquote>
848
+ "HuggingFace represents the best of what open source and collaborative development can achieve. It proves that advancing AI does not require hoarding knowledge behind corporate walls but flourishes when we share, collaborate, and build together."
849
+ </blockquote>
850
+
851
+ <p>
852
+ The platform's impact extends beyond technical contributions. It has shaped research culture toward openness and reproducibility. It has educated a generation of AI practitioners. It has demonstrated sustainable business models compatible with open source values.
853
+ </p>
854
+
855
+ <p>
856
+ Challenges remain around environmental sustainability, safety, bias, and governance. These are not unique to HuggingFace but reflect broader tensions in AI development. The platform's commitment to transparency and community engagement positions it to help address these challenges constructively.
857
+ </p>
858
+
859
+ <p>
860
+ As artificial intelligence becomes increasingly central to technology and society, the infrastructure supporting AI development grows in importance. HuggingFace has established itself as essential infrastructure, the place where models are shared, improved, and deployed. The platform's continued evolution will shape not just how AI is built but what AI becomes and who gets to participate in creating it.
861
+ </p>
862
+
863
+ <p>
864
+ For anyone working with AI today, whether researcher, developer, student, or enthusiast, HuggingFace is indispensable. It represents the collaborative, open future of AI development where progress comes not from isolated labs but from global communities working together to push the boundaries of what is possible.
865
+ </p>
866
+
867
+ <p>
868
+ <strong>The golden age of accessible AI has arrived, and HuggingFace is the platform making it possible.</strong>
869
+ </p>
post/learning the basics of c programming.md ADDED
@@ -0,0 +1,218 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ title: Learning the Basics of C Programming
3
+ date: 2017-01-01
4
+ description: In programming, there are many programming languages. One of the languages I studied is the C programming language. In this article, I will introduce the basic concepts of C programming that I have learned. The goal is to give beginners a clear and correct foundation before moving on to more advanced topics.
5
+ author: Hadad Darajat
6
+ tags:
7
+ - c
8
+ - programming
9
+ - introduction
10
+ ---
11
+
12
+ <p>
13
+ In the world of software development, programming languages serve as the foundation
14
+ for creating applications. This article will introduce you to the fundamental concepts
15
+ of C programming language, one of the most influential languages in computing history.
16
+ </p>
17
+
18
+ <h2>1. Headers</h2>
19
+
20
+ <p>
21
+ Every C program begins with a header section. Headers serve as libraries that contain
22
+ predefined functions and commands that we will use throughout our program. Think of
23
+ headers as toolboxes that store various tools we need.
24
+ </p>
25
+
26
+ <p>Example of a header declaration :</p>
27
+
28
+ ```c
29
+ #include <stdio.h>
30
+ ```
31
+
32
+ <p>
33
+ The header declaration always starts with <code>#include</code> followed by the library
34
+ name enclosed in angle brackets. For example, if we need to use input and output functions
35
+ like <code>printf</code>, we must include the <code>stdio.h</code> header.
36
+ </p>
37
+
38
+ <p>Common headers in C programming :</p>
39
+
40
+ <ul>
41
+ <li><code>stdio.h</code> for standard input and output functions</li>
42
+ <li><code>stdlib.h</code> for standard library functions</li>
43
+ <li><code>string.h</code> for string manipulation functions</li>
44
+ <li><code>math.h</code> for mathematical functions</li>
45
+ </ul>
46
+
47
+ <h2>2. Functions</h2>
48
+
49
+ <p>
50
+ After the header section comes the body of the program, which consists of functions.
51
+ The most essential function in C is the <code>main()</code> function, which serves as
52
+ the entry point of every C program.
53
+ </p>
54
+
55
+ <p>Basic structure of a function :</p>
56
+
57
+ ```c
58
+ int main(void)
59
+ {
60
+ // Your code goes here
61
+ return 0;
62
+ }
63
+ ```
64
+
65
+ <p>
66
+ The curly braces <code>{</code> and <code>}</code> define the beginning and end of
67
+ the function body. All statements within the function must be placed between these braces.
68
+ The <code>return 0</code> statement indicates that the program has executed successfully.
69
+ </p>
70
+
71
+ <h2>3. Variables and Data Types</h2>
72
+
73
+ <p>
74
+ Variables are containers used to store data values in a program. Each variable must have
75
+ a specific data type that determines what kind of value it can hold.
76
+ </p>
77
+
78
+ <p>
79
+ In C, variables must be declared before they can be used. For example, to create a program
80
+ that calculates the area of a rectangle using the formula <strong>Area = length × width</strong>,
81
+ we need to declare the following variables.
82
+ </p>
83
+
84
+ <ul>
85
+ <li><code>area</code> to store the calculated area</li>
86
+ <li><code>length</code> to store the length value</li>
87
+ <li><code>width</code> to store the width value</li>
88
+ </ul>
89
+
90
+ <p>Example of variable declaration :</p>
91
+
92
+ ```c
93
+ int area;
94
+ int length;
95
+ int width;
96
+ ```
97
+
98
+ <p>
99
+ The keyword <code>int</code> represents the integer data type, which stores whole numbers.
100
+ Common data types in C include.
101
+ </p>
102
+
103
+ <ul>
104
+ <li><code>int</code> for integers or whole numbers</li>
105
+ <li><code>float</code> for single precision floating point numbers</li>
106
+ <li><code>double</code> for double precision floating point numbers</li>
107
+ <li><code>char</code> for single characters</li>
108
+ </ul>
109
+
110
+ <h2>4. Input and Output Commands</h2>
111
+
112
+ <p>
113
+ To perform input and output operations, we need to include the <code>stdio.h</code> header.
114
+ This header provides functions for reading user input and displaying output.
115
+ </p>
116
+
117
+ <h3>The printf Function</h3>
118
+
119
+ <p>
120
+ The <code>printf</code> function is used to display output to the screen :
121
+ </p>
122
+
123
+ ```c
124
+ printf("Welcome to C Programming\n");
125
+ ```
126
+
127
+ <p>
128
+ This statement displays the text "Welcome to C Programming" on the screen.
129
+ The <code>\n</code> character creates a new line after the text.
130
+ </p>
131
+
132
+ <h3>The scanf Function</h3>
133
+
134
+ <p>
135
+ The <code>scanf</code> function is used to read input from the user :
136
+ </p>
137
+
138
+ ```c
139
+ scanf("%d", &area);
140
+ ```
141
+
142
+ <p>
143
+ This statement reads an integer value from the user and stores it in the variable
144
+ <code>area</code>. The format specifier <code>%d</code> indicates that an integer
145
+ value is expected. The ampersand symbol <code>&</code> is the address operator,
146
+ which specifies where the input value should be stored in memory.
147
+ </p>
148
+
149
+ <p>Common format specifiers :</p>
150
+
151
+ <ul>
152
+ <li><code>%d</code> for integers</li>
153
+ <li><code>%f</code> for floating point numbers</li>
154
+ <li><code>%c</code> for characters</li>
155
+ <li><code>%s</code> for strings</li>
156
+ </ul>
157
+
158
+ <h2>5. Complete Example Program</h2>
159
+
160
+ <p>
161
+ The following program calculates the area of a rectangle. It prompts the user to
162
+ enter the length and width values, then computes and displays the result :
163
+ </p>
164
+
165
+ ```c
166
+ #include <stdio.h>
167
+
168
+ int main(void)
169
+ {
170
+ int area;
171
+ int length;
172
+ int width;
173
+
174
+ printf("Enter the length of the rectangle: ");
175
+ scanf("%d", &length);
176
+
177
+ printf("Enter the width of the rectangle: ");
178
+ scanf("%d", &width);
179
+
180
+ area = length * width;
181
+
182
+ printf("Area = %d\n", area);
183
+
184
+ return 0;
185
+ }
186
+ ```
187
+
188
+ <h3>Code Explanation</h3>
189
+
190
+ <ol>
191
+ <li>Include the <code>stdio.h</code> header for input and output functions.</li>
192
+ <li>Define the <code>main</code> function as the program entry point.</li>
193
+ <li>Declare three integer variables for area, length, and width.</li>
194
+ <li>Display a prompt asking the user to enter the length.</li>
195
+ <li>Read the length value from user input.</li>
196
+ <li>Display a prompt asking the user to enter the width.</li>
197
+ <li>Read the width value from user input.</li>
198
+ <li>Calculate the area by multiplying length and width.</li>
199
+ <li>Display the calculated area.</li>
200
+ <li>Return 0 to indicate successful program execution.</li>
201
+ </ol>
202
+
203
+ <h2>Conclusion</h2>
204
+
205
+ <p>
206
+ This article covered the fundamental concepts of C programming, including headers,
207
+ functions, variables, data types, and input output operations. Understanding these
208
+ basics is essential before progressing to more advanced topics. Practice writing
209
+ simple programs to strengthen your understanding of these concepts.
210
+ </p>
211
+
212
+ ---
213
+
214
+ <p style="font-size:10px;">
215
+ This article is a mirror of the original post written in Indonesian several years ago, when I was deeply learning and exploring programming.
216
+ Original post can be found at <a href="https://hadaddarajat.blogspot.com/2017/01/belajar-dasar-pemrograman-bahasa-c.html" target="_blank">
217
+ https://hadaddarajat.blogspot.com/2017/01/belajar-dasar-pemrograman-bahasa-c.html</a>
218
+ </p>
post/llm bias and hallucinations.md ADDED
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1
+ ---
2
+ title: How Dangerous Are Hallucinations and Bias in Large Language Models
3
+ date: 2026-01-16
4
+ description: Large Language Models have rapidly transformed from research curiosities into tools that millions of people rely on daily. From ChatGPT to Claude, from Gemini to LLaMA, these systems assist with writing, coding, research, education, healthcare decisions, legal analysis, and countless other tasks.
5
+ author: Hadad Darajat
6
+ tags:
7
+ - llm
8
+ - ai
9
+ - bias
10
+ - hallucinations
11
+ ---
12
+
13
+ <p>
14
+ Large Language Models have rapidly transformed from research curiosities into tools that millions of people rely on daily. From ChatGPT to Claude, from Gemini to LLaMA, these systems assist with writing, coding, research, education, healthcare decisions, legal analysis, and countless other tasks. Yet beneath their impressive capabilities lurk two fundamental problems that threaten to undermine their usefulness and cause real harm: <strong>hallucinations</strong> and <strong>bias</strong>.
15
+ </p>
16
+
17
+ <p>
18
+ These are not minor technical glitches that will be solved with the next model update. They are deeply rooted in how LLMs work, what they learn from, and how they generate responses. Understanding these problems, their causes, their consequences, and our limited ability to fully solve them, is essential for anyone using, building, or making decisions about AI systems.
19
+ </p>
20
+
21
+ <blockquote>
22
+ "The most dangerous aspect of AI hallucinations is not that they happen, but that they happen with complete confidence. The model does not know that it does not know, and neither does the user until the damage is done."
23
+ </blockquote>
24
+
25
+ <h2>Understanding Hallucinations in LLMs</h2>
26
+
27
+ <p>
28
+ In the context of large language models, a <strong>hallucination</strong> refers to the generation of content that is factually incorrect, nonsensical, or entirely fabricated, presented with the same confidence as accurate information. The term borrows from psychology, where hallucinations are perceptions without external stimuli. Similarly, LLMs produce outputs without grounding in reality.
29
+ </p>
30
+
31
+ <h3>What Hallucinations Look Like</h3>
32
+
33
+ <p>
34
+ Hallucinations manifest in various forms, ranging from subtle inaccuracies to complete fabrications:
35
+ </p>
36
+
37
+ <p>
38
+ <strong>Factual errors</strong> include incorrect dates, wrong names, false statistics, and inaccurate descriptions of events. An LLM might confidently state that a historical event occurred in the wrong year, attribute a quote to the wrong person, or provide incorrect scientific data.
39
+ </p>
40
+
41
+ <p>
42
+ <strong>Fabricated citations</strong> are particularly insidious in academic and professional contexts. LLMs frequently generate references to papers, books, or articles that do not exist. The citations look perfectly plausible, complete with author names, journal titles, publication years, and page numbers, but upon verification, they are entirely invented.
43
+ </p>
44
+
45
+ <p>
46
+ <strong>Invented entities</strong> involve creating people, places, organizations, or events that have never existed. An LLM might describe a fictional professor at a real university, invent a company that supposedly manufactures a product, or create biographical details for real people that are completely false.
47
+ </p>
48
+
49
+ <p>
50
+ <strong>Logical inconsistencies</strong> occur when the model contradicts itself within a single response or across a conversation. It might claim something is true in one paragraph and false in another, or provide reasoning that does not follow from its premises.
51
+ </p>
52
+
53
+ <p>
54
+ <strong>Confident uncertainty</strong> describes situations where the model should express uncertainty but instead provides definitive answers. Rather than saying "I don't know" or "I'm not sure," it invents a plausible sounding response.
55
+ </p>
56
+
57
+ <h3>Why Hallucinations Occur</h3>
58
+
59
+ <p>
60
+ Understanding why LLMs hallucinate requires understanding how they work. These models are trained on massive text corpora to predict the next token in a sequence. They learn statistical patterns in language, capturing relationships between words, phrases, and concepts. However, they do not have:
61
+ </p>
62
+
63
+ <ul>
64
+ <li><strong>Access to ground truth</strong> or a database of verified facts they can query</li>
65
+ <li><strong>Understanding of truth</strong> in any meaningful sense, only patterns in text</li>
66
+ <li><strong>Awareness of their knowledge boundaries</strong> or what they do and do not know</li>
67
+ <li><strong>Real world grounding</strong> connecting language to physical reality</li>
68
+ <li><strong>Temporal awareness</strong> of when information might be outdated</li>
69
+ </ul>
70
+
71
+ <p>
72
+ When an LLM generates text, it is essentially asking: <em>"Given this context, what words would statistically likely come next?"</em> This works remarkably well for many tasks, but it means the model can generate text that sounds correct without being correct. It optimizes for plausibility, not truth.
73
+ </p>
74
+
75
+ <p>
76
+ Consider what happens when you ask about an obscure topic with limited training data. The model has seen patterns about how experts discuss topics, how citations are formatted, and how confident statements are structured. It applies these patterns even when it lacks the specific knowledge to fill them accurately.
77
+ </p>
78
+
79
+ ```
80
+ User: Who wrote the paper "Quantum Entanglement in Neural Networks"
81
+ published in Nature in 2019?
82
+
83
+ LLM Response: The paper "Quantum Entanglement in Neural Networks"
84
+ was authored by Dr. Sarah Chen and Professor Michael Roberts from
85
+ MIT, published in Nature in March 2019. It explored the
86
+ theoretical connections between quantum entanglement principles
87
+ and information processing in deep neural networks.
88
+
89
+ Reality: This paper does not exist. The authors are fabricated.
90
+ The model generated a plausible-sounding response based on
91
+ patterns it learned about academic papers, MIT, and the topics
92
+ mentioned.
93
+ ```
94
+
95
+ <h3>The Confidence Problem</h3>
96
+
97
+ <p>
98
+ Perhaps the most dangerous aspect of hallucinations is that LLMs express them with the same confidence as accurate information. Unlike humans, who might hedge with phrases like "I think" or "I'm not sure," LLMs often present fabricated information definitively.
99
+ </p>
100
+
101
+ <p>
102
+ This confidence is not intentional deception but an artifact of training. The model learned from text where confident, declarative statements are common. It was not trained to express calibrated uncertainty about its own knowledge. The result is that users cannot distinguish reliable information from hallucinations based on how the model presents them.
103
+ </p>
104
+
105
+ <blockquote>
106
+ "An LLM will tell you the wrong answer with exactly the same tone it uses to tell you the right answer. There is no tell, no hesitation, no warning. That is what makes it so dangerous."
107
+ </blockquote>
108
+
109
+ <h2>Understanding Bias in LLMs</h2>
110
+
111
+ <p>
112
+ <strong>Bias</strong> in large language models refers to systematic tendencies that favor certain perspectives, groups, or outcomes over others in ways that may be unfair, harmful, or unrepresentative. Unlike hallucinations which produce false information, bias produces skewed information that reflects and potentially amplifies prejudices present in training data and society.
113
+ </p>
114
+
115
+ <h3>Types of Bias in LLMs</h3>
116
+
117
+ <p>
118
+ Bias manifests in multiple forms, each with different causes and consequences:
119
+ </p>
120
+
121
+ <p>
122
+ <strong>Demographic bias</strong> involves differential treatment based on characteristics like gender, race, ethnicity, age, religion, nationality, or disability status. Models might associate certain professions with specific genders, use different tones when discussing different ethnic groups, or make assumptions based on names that suggest particular backgrounds.
123
+ </p>
124
+
125
+ <p>
126
+ <strong>Cultural and geographic bias</strong> reflects the overrepresentation of certain cultures, typically Western and English speaking, in training data. Models may have deep knowledge about American history but superficial understanding of African history. They may understand cultural references from one region while misinterpreting those from another.
127
+ </p>
128
+
129
+ <p>
130
+ <strong>Temporal bias</strong> arises from training data cutoffs and the predominance of recent content online. Models may have detailed knowledge of recent events but limited understanding of historical periods. They may also reflect attitudes and language norms from the period of their training data.
131
+ </p>
132
+
133
+ <p>
134
+ <strong>Socioeconomic bias</strong> reflects whose voices and perspectives are represented in training data. Content from well resourced, highly educated populations is overrepresented compared to perspectives from economically marginalized communities.
135
+ </p>
136
+
137
+ <p>
138
+ <strong>Ideological and political bias</strong> can emerge from imbalances in training data or from alignment processes that inadvertently favor certain viewpoints. Models may express opinions on contested topics or frame issues in ways that reflect particular ideological assumptions.
139
+ </p>
140
+
141
+ <p>
142
+ <strong>Occupational and professional bias</strong> includes assumptions about who holds certain roles and the relative value of different types of work. A model might assume doctors are male or nurses are female, or show more respect for white collar than blue collar professions.
143
+ </p>
144
+
145
+ <h3>Sources of Bias</h3>
146
+
147
+ <p>
148
+ Bias enters LLMs through multiple pathways:
149
+ </p>
150
+
151
+ <p>
152
+ <strong>Training data reflects society.</strong> LLMs learn from text produced by humans, and that text contains the biases, prejudices, and unequal representations present in society. If historical texts underrepresent certain groups or portray them negatively, the model learns these patterns.
153
+ </p>
154
+
155
+ <p>
156
+ <strong>Data collection is not neutral.</strong> The internet, the primary source of training data, is not a representative sample of human knowledge or perspectives. English content dominates. Certain topics, communities, and viewpoints are overrepresented while others are marginalized or absent.
157
+ </p>
158
+
159
+ <p>
160
+ <strong>Annotation and labeling introduce human judgment.</strong> When humans label data for training, particularly for reinforcement learning from human feedback, their biases influence what the model learns to prefer or avoid.
161
+ </p>
162
+
163
+ <p>
164
+ <strong>Optimization objectives may encode bias.</strong> Training objectives like engagement or user satisfaction can amplify biases if biased content is more engaging or satisfying to certain user populations.
165
+ </p>
166
+
167
+ <p>
168
+ <strong>Feedback loops compound effects.</strong> As AI generated content increasingly becomes training data for future models, biases can compound over generations in what researchers call "model collapse."
169
+ </p>
170
+
171
+ <h3>Measuring and Detecting Bias</h3>
172
+
173
+ <p>
174
+ Researchers have developed various methods to identify bias in LLMs:
175
+ </p>
176
+
177
+ ```python
178
+ # Simple bias probe example
179
+ # Testing gender bias in occupation associations
180
+
181
+ prompts = [
182
+ "The doctor walked into the room. He",
183
+ "The doctor walked into the room. She",
184
+ "The nurse walked into the room. He",
185
+ "The nurse walked into the room. She",
186
+ ]
187
+
188
+ # Compare probability distributions for continuations
189
+ # Significant differences suggest gender-occupation bias
190
+
191
+ # More sophisticated tests use templates
192
+ templates = [
193
+ "The [OCCUPATION] said [PRONOUN] would",
194
+ "[NAME] is a [OCCUPATION]. [PRONOUN] is",
195
+ ]
196
+
197
+ # Substituting different names, pronouns, and occupations
198
+ # reveals patterns of differential treatment
199
+ ```
200
+
201
+ <p>
202
+ Common bias evaluation approaches include:
203
+ </p>
204
+
205
+ <ul>
206
+ <li><strong>Prompt based testing</strong> using template sentences to probe associations</li>
207
+ <li><strong>Embedding analysis</strong> examining how concepts cluster in model representations</li>
208
+ <li><strong>Counterfactual evaluation</strong> comparing outputs when demographic features are swapped</li>
209
+ <li><strong>Benchmark datasets</strong> standardized tests like WinoBias, StereoSet, and BBQ</li>
210
+ <li><strong>Human evaluation</strong> expert assessment of generated content for bias</li>
211
+ <li><strong>Downstream impact measurement</strong> testing how bias affects real applications</li>
212
+ </ul>
213
+
214
+ <h2>Real World Harms and Case Studies</h2>
215
+
216
+ <p>
217
+ The dangers of hallucinations and bias are not theoretical. They have caused documented harm across multiple domains and will continue to do so as LLM adoption expands.
218
+ </p>
219
+
220
+ <h3>Legal System Failures</h3>
221
+
222
+ <p>
223
+ In 2023, a New York attorney named Steven Schwartz used ChatGPT to research a legal case and submitted a brief containing <strong>six completely fabricated case citations</strong>. The invented cases included nonexistent plaintiffs, defendants, and legal precedents. When opposing counsel could not locate the cases, and the judge demanded verification, Schwartz admitted he had used ChatGPT and trusted its outputs without verification.
224
+ </p>
225
+
226
+ <p>
227
+ The attorney was sanctioned and fined. But consider the broader implications:
228
+ </p>
229
+
230
+ <ul>
231
+ <li>What if the opposing counsel had not checked?</li>
232
+ <li>What if the fabricated precedents had influenced the ruling?</li>
233
+ <li>How many undetected hallucinations exist in legal documents?</li>
234
+ <li>What happens when defendants cannot afford lawyers who carefully verify AI outputs?</li>
235
+ </ul>
236
+
237
+ <blockquote>
238
+ "I did not comprehend that ChatGPT could fabricate cases."
239
+ <br><em>- Steven Schwartz, in his admission to the court</em>
240
+ </blockquote>
241
+
242
+ <p>
243
+ This case became famous because it was caught, but it represents a systemic risk. Legal professionals increasingly use AI tools for research, drafting, and analysis. Each uncaught hallucination potentially undermines justice.
244
+ </p>
245
+
246
+ <h3>Healthcare Misinformation</h3>
247
+
248
+ <p>
249
+ Studies have documented LLMs providing dangerous medical advice:
250
+ </p>
251
+
252
+ <ul>
253
+ <li><strong>Incorrect drug dosages</strong> that could cause harm or death</li>
254
+ <li><strong>Fabricated drug interactions</strong> warning about nonexistent risks or missing real ones</li>
255
+ <li><strong>Invented treatment protocols</strong> that sound plausible but lack evidence</li>
256
+ <li><strong>Misdiagnosis suggestions</strong> based on symptom descriptions</li>
257
+ <li><strong>Outdated medical guidance</strong> reflecting superseded standards of care</li>
258
+ </ul>
259
+
260
+ <p>
261
+ Research published in JAMA found that when asked about cancer treatments, LLMs sometimes provided recommendations that contradicted current guidelines or invented studies supporting particular approaches. The danger is amplified because patients seeking second opinions or those in areas with limited healthcare access might trust AI responses.
262
+ </p>
263
+
264
+ <p>
265
+ Bias compounds these risks. Studies have shown that AI systems, including LLMs, may provide different quality responses when patient descriptions suggest different demographic backgrounds. Pain management recommendations, treatment urgency assessments, and diagnostic considerations can all vary based on implicit demographic cues.
266
+ </p>
267
+
268
+ <h3>Financial and Investment Harm</h3>
269
+
270
+ <p>
271
+ The financial sector faces unique risks from LLM failures:
272
+ </p>
273
+
274
+ <p>
275
+ <strong>Fabricated financial data</strong> including invented stock prices, false earnings reports, or nonexistent market events can mislead investors. An LLM confidently stating that a company reported specific earnings creates investment risk if that information is false.
276
+ </p>
277
+
278
+ <p>
279
+ <strong>Biased financial advice</strong> can systematically disadvantage certain groups. If a model learned from data where investment advice differed by demographic group, it might perpetuate those patterns.
280
+ </p>
281
+
282
+ <p>
283
+ <strong>Regulatory compliance failures</strong> occur when organizations rely on AI generated analysis that contains errors. Financial regulations require accuracy, and hallucinations can create legal liability.
284
+ </p>
285
+
286
+ <h3>Education and Academic Integrity</h3>
287
+
288
+ <p>
289
+ Students increasingly use LLMs for research and writing assistance. The consequences of hallucinations include:
290
+ </p>
291
+
292
+ <ul>
293
+ <li><strong>Learning false information</strong> that becomes embedded in understanding</li>
294
+ <li><strong>Citing nonexistent sources</strong> undermining academic integrity</li>
295
+ <li><strong>Building on false premises</strong> in research projects</li>
296
+ <li><strong>Developing misplaced confidence</strong> in AI as an authoritative source</li>
297
+ </ul>
298
+
299
+ <p>
300
+ Bias in educational AI creates additional concerns. If models have less knowledge about certain historical figures, cultures, or perspectives, students using them receive an incomplete and skewed education. Those gaps themselves are educational failures.
301
+ </p>
302
+
303
+ <h3>Journalism and Information Ecosystem</h3>
304
+
305
+ <p>
306
+ News organizations and content creators using LLMs risk:
307
+ </p>
308
+
309
+ <ul>
310
+ <li><strong>Publishing false information</strong> as factual news</li>
311
+ <li><strong>Amplifying existing narratives</strong> through biased framings</li>
312
+ <li><strong>Underrepresenting perspectives</strong> absent from training data</li>
313
+ <li><strong>Eroding trust</strong> when errors are discovered</li>
314
+ </ul>
315
+
316
+ <p>
317
+ Several news organizations have published AI generated content containing factual errors, leading to retractions and damaged credibility. As the information ecosystem increasingly includes AI generated content, distinguishing reliable from unreliable sources becomes harder for consumers.
318
+ </p>
319
+
320
+ <h3>Employment and Hiring</h3>
321
+
322
+ <p>
323
+ LLMs used in hiring processes can embed and amplify bias:
324
+ </p>
325
+
326
+ <p>
327
+ <strong>Resume screening</strong> may favor candidates whose backgrounds match patterns in biased training data. Names, educational institutions, and even writing styles can trigger differential treatment.
328
+ </p>
329
+
330
+ <p>
331
+ <strong>Interview question generation</strong> might produce questions that disadvantage certain groups or assess irrelevant characteristics.
332
+ </p>
333
+
334
+ <p>
335
+ <strong>Candidate evaluation</strong> can reflect biased assumptions about what makes a good employee, favoring those who match historically privileged profiles.
336
+ </p>
337
+
338
+ <p>
339
+ Research has demonstrated that LLMs show measurable bias when evaluating identical qualifications attributed to names suggesting different genders or ethnicities.
340
+ </p>
341
+
342
+ ```
343
+ Experiment: Submit identical resumes to an LLM evaluator
344
+ with only the name changed
345
+
346
+ Results:
347
+ - "James Smith" rated 4.2/5.0 for software engineering role
348
+ - "Jamal Washington" rated 3.8/5.0 for identical resume
349
+ - "Emily Chen" rated 4.0/5.0 for identical resume
350
+ - "María García" rated 3.9/5.0 for identical resume
351
+
352
+ The qualifications were identical. The evaluations were not.
353
+ ```
354
+
355
+ <h2>The Scale of the Problem</h2>
356
+
357
+ <p>
358
+ What makes hallucinations and bias particularly dangerous is the <strong>scale at which LLMs operate</strong>. These are not isolated incidents but systemic issues affecting millions of interactions daily.
359
+ </p>
360
+
361
+ <h3>Volume and Velocity</h3>
362
+
363
+ <p>
364
+ Consider the numbers:
365
+ </p>
366
+
367
+ <ul>
368
+ <li>ChatGPT alone has over 100 million weekly active users</li>
369
+ <li>Each user may have dozens of interactions per session</li>
370
+ <li>Enterprise deployments serve additional millions of end users</li>
371
+ <li>AI generated content increasingly populates the internet</li>
372
+ </ul>
373
+
374
+ <p>
375
+ If even a small percentage of responses contain hallucinations or exhibit bias, the absolute number of harmful outputs is enormous. A 1% hallucination rate across 100 million users generating 10 queries each means <strong>10 million potentially harmful responses weekly</strong> from a single platform.
376
+ </p>
377
+
378
+ <h3>Compounding Effects</h3>
379
+
380
+ <p>
381
+ Errors compound in several ways:
382
+ </p>
383
+
384
+ <p>
385
+ <strong>Downstream propagation</strong> occurs when AI generated content becomes input for other processes. A hallucinated fact in a report gets cited in other documents, spreading misinformation.
386
+ </p>
387
+
388
+ <p>
389
+ <strong>Training data contamination</strong> happens as AI generated content increasingly enters the corpus used to train future models. Hallucinations and biases can become self reinforcing.
390
+ </p>
391
+
392
+ <p>
393
+ <strong>Trust calibration failure</strong> develops when users experience many correct outputs and lower their guard. They stop verifying, making occasional errors more damaging.
394
+ </p>
395
+
396
+ <p>
397
+ <strong>Automation complacency</strong> sets in as organizations rely more heavily on AI. Manual checks decrease, and errors pass through systems uncaught.
398
+ </p>
399
+
400
+ <h3>Asymmetric Impact</h3>
401
+
402
+ <p>
403
+ The harms of hallucinations and bias are not distributed equally:
404
+ </p>
405
+
406
+ <ul>
407
+ <li><strong>Marginalized communities</strong> suffer more from bias because they are more likely to be misrepresented or stereotyped in training data</li>
408
+ <li><strong>Less resourced users</strong> cannot afford to verify AI outputs or access alternative sources</li>
409
+ <li><strong>Non English speakers</strong> encounter lower quality, more error prone model performance</li>
410
+ <li><strong>High stakes situations</strong> like legal or medical contexts amplify harm from errors</li>
411
+ <li><strong>Populations with less AI literacy</strong> may not understand limitations or appropriate uses</li>
412
+ </ul>
413
+
414
+ <blockquote>
415
+ "AI bias is not a bug to be fixed but a mirror reflecting society's inequities. The question is whether we use that mirror to perpetuate those inequities or to reveal and address them."
416
+ </blockquote>
417
+
418
+ <h2>Why These Problems Are Hard to Solve</h2>
419
+
420
+ <p>
421
+ Despite significant research and engineering effort, hallucinations and bias remain persistent challenges. Understanding why reveals deep limitations in current approaches.
422
+ </p>
423
+
424
+ <h3>The Fundamental Nature of LLMs</h3>
425
+
426
+ <p>
427
+ LLMs are statistical pattern matchers trained on text. They do not have:
428
+ </p>
429
+
430
+ <ul>
431
+ <li><strong>World models</strong> that represent reality independently from language about reality</li>
432
+ <li><strong>Verification mechanisms</strong> that check claims against ground truth</li>
433
+ <li><strong>Epistemic humility</strong> or awareness of what they do and do not know</li>
434
+ <li><strong>Causal reasoning</strong> distinguishing correlation from causation</li>
435
+ <li><strong>Intentionality</strong> or goals beyond predicting likely next tokens</li>
436
+ </ul>
437
+
438
+ <p>
439
+ Hallucinations are not a failure mode to be eliminated but a natural consequence of how these systems work. Asking an LLM not to hallucinate is like asking a calculator not to return answers for invalid inputs, it requires fundamentally different architecture.
440
+ </p>
441
+
442
+ <h3>The Bias Paradox</h3>
443
+
444
+ <p>
445
+ Addressing bias faces inherent tensions:
446
+ </p>
447
+
448
+ <p>
449
+ <strong>Representation vs. accuracy.</strong> Training data reflects reality, including unfortunate realities about how different groups are represented in society. A model that accurately captures patterns in its training data will reproduce biases present in that data. But a model that artificially adjusts representations may produce less accurate outputs.
450
+ </p>
451
+
452
+ <p>
453
+ <strong>Fairness definitions conflict.</strong> Different mathematical definitions of fairness are provably incompatible. You cannot simultaneously achieve demographic parity, equalized odds, and calibration in most real world scenarios. Choosing which fairness criterion to optimize is a value judgment, not a technical decision.
454
+ </p>
455
+
456
+ <p>
457
+ <strong>Debiasing has limits.</strong> Techniques to reduce bias often trade off against other objectives like accuracy or coherence. Aggressive debiasing can make models less useful while not fully eliminating bias.
458
+ </p>
459
+
460
+ <h3>Detection Challenges</h3>
461
+
462
+ <p>
463
+ Identifying hallucinations and bias is itself difficult:
464
+ </p>
465
+
466
+ <p>
467
+ <strong>Ground truth is not always available.</strong> For many queries, there is no easily accessible source of truth to compare against. Verifying factual claims requires expertise and resources.
468
+ </p>
469
+
470
+ <p>
471
+ <strong>Bias is context dependent.</strong> What constitutes bias depends on the application, the stakeholders, and value judgments about what fair outcomes look like. There is no universal, objective test for bias.
472
+ </p>
473
+
474
+ <p>
475
+ <strong>Adversarial robustness is limited.</strong> Users can often find prompts that elicit hallucinations or biased outputs even from models designed to resist them. The space of possible inputs is too vast to secure completely.
476
+ </p>
477
+
478
+ <h3>Mitigation Tradeoffs</h3>
479
+
480
+ <p>
481
+ Every mitigation strategy has costs:
482
+ </p>
483
+
484
+ <ul>
485
+ <li><strong>Refusing to answer</strong> reduces utility and frustrates users</li>
486
+ <li><strong>Heavy caveats</strong> make outputs less useful and readable</li>
487
+ <li><strong>Retrieval augmentation</strong> adds complexity and latency while not eliminating errors</li>
488
+ <li><strong>Human oversight</strong> does not scale and introduces its own biases</li>
489
+ <li><strong>Fine tuning for safety</strong> can reduce capability and introduce new problems</li>
490
+ </ul>
491
+
492
+ <h2>Current Mitigation Strategies</h2>
493
+
494
+ <p>
495
+ Despite the challenges, researchers and practitioners have developed various approaches to reduce harm from hallucinations and bias.
496
+ </p>
497
+
498
+ <h3>Retrieval Augmented Generation (RAG)</h3>
499
+
500
+ <p>
501
+ RAG systems ground LLM responses in retrieved documents, reducing reliance on potentially flawed parametric knowledge.
502
+ </p>
503
+
504
+ ```python
505
+ # Simplified RAG architecture
506
+ from transformers import AutoTokenizer, AutoModel
507
+ import faiss
508
+
509
+ class RAGSystem:
510
+ def __init__(self, documents, model_name):
511
+ self.tokenizer = AutoTokenizer.from_pretrained(model_name)
512
+ self.model = AutoModel.from_pretrained(model_name)
513
+ self.index = self.build_index(documents)
514
+ self.documents = documents
515
+
516
+ def build_index(self, documents):
517
+ # Embed documents and build vector index
518
+ embeddings = self.embed(documents)
519
+ index = faiss.IndexFlatL2(embeddings.shape[1])
520
+ index.add(embeddings)
521
+ return index
522
+
523
+ def retrieve(self, query, k=5):
524
+ # Find most relevant documents
525
+ query_embedding = self.embed([query])
526
+ distances, indices = self.index.search(query_embedding, k)
527
+ return [self.documents[i] for i in indices[0]]
528
+
529
+ def generate(self, query):
530
+ # Retrieve context and generate grounded response
531
+ context = self.retrieve(query)
532
+ prompt = f"Context: {context}\n\nQuestion: {query}\n\nAnswer:"
533
+ # Generate response using LLM with retrieved context
534
+ return self.llm_generate(prompt)
535
+ ```
536
+
537
+ <p>
538
+ RAG reduces but does not eliminate hallucinations. The model can still:
539
+ </p>
540
+
541
+ <ul>
542
+ <li>Misinterpret retrieved documents</li>
543
+ <li>Generate content not supported by context</li>
544
+ <li>Retrieve irrelevant or incorrect documents</li>
545
+ <li>Combine retrieved information in wrong ways</li>
546
+ </ul>
547
+
548
+ <h3>Constitutional AI and RLHF</h3>
549
+
550
+ <p>
551
+ <strong>Reinforcement Learning from Human Feedback</strong> and related techniques train models to prefer helpful, harmless, and honest outputs. Constitutional AI extends this with explicit principles the model should follow.
552
+ </p>
553
+
554
+ <p>
555
+ These approaches have meaningfully improved model behavior but face limitations:
556
+ </p>
557
+
558
+ <ul>
559
+ <li>Human raters have their own biases</li>
560
+ <li>Optimization can lead to surface level compliance without genuine improvement</li>
561
+ <li>Models may learn to hide rather than eliminate problematic behaviors</li>
562
+ <li>Adversarial prompts can still elicit unwanted outputs</li>
563
+ </ul>
564
+
565
+ <h3>Uncertainty Quantification</h3>
566
+
567
+ <p>
568
+ Researchers have developed methods to estimate model confidence:
569
+ </p>
570
+
571
+ <ul>
572
+ <li><strong>Token probability analysis</strong> examining how confident the model is about each word</li>
573
+ <li><strong>Consistency checking</strong> sampling multiple responses and measuring agreement</li>
574
+ <li><strong>Calibration training</strong> teaching models to express appropriate uncertainty</li>
575
+ <li><strong>Selective prediction</strong> abstaining when confidence is low</li>
576
+ </ul>
577
+
578
+ <p>
579
+ However, uncertainty estimates remain imperfect. Models can be confidently wrong and uncertain about correct answers. Current techniques provide useful signals but not reliable guarantees.
580
+ </p>
581
+
582
+ <h3>Fact Checking and Verification Pipelines</h3>
583
+
584
+ <p>
585
+ Some systems implement post hoc verification:
586
+ </p>
587
+
588
+ <ol>
589
+ <li>Generate initial response</li>
590
+ <li>Extract factual claims</li>
591
+ <li>Verify claims against reliable sources</li>
592
+ <li>Revise or flag unverified claims</li>
593
+ </ol>
594
+
595
+ <p>
596
+ This approach catches some errors but adds latency, cost, and complexity. It also relies on having reliable sources available for verification, which is not always the case.
597
+ </p>
598
+
599
+ <h3>Diverse Training Data and Representation</h3>
600
+
601
+ <p>
602
+ Addressing bias through data involves:
603
+ </p>
604
+
605
+ <ul>
606
+ <li><strong>Curating more representative datasets</strong> including underrepresented voices and perspectives</li>
607
+ <li><strong>Balancing demographic representation</strong> in training examples</li>
608
+ <li><strong>Including multilingual and multicultural content</strong> beyond English and Western sources</li>
609
+ <li><strong>Filtering harmful content</strong> while preserving useful information</li>
610
+ </ul>
611
+
612
+ <p>
613
+ Data interventions help but face practical limits. Perfect representation is impossible, and decisions about what to include or exclude involve value judgments.
614
+ </p>
615
+
616
+ <h3>Red Teaming and Adversarial Testing</h3>
617
+
618
+ <p>
619
+ Organizations deploy teams to find failure modes before users do:
620
+ </p>
621
+
622
+ <ul>
623
+ <li><strong>Manual red teaming</strong> with human experts probing for problems</li>
624
+ <li><strong>Automated adversarial testing</strong> using AI to find AI failures</li>
625
+ <li><strong>Crowd sourced bug bounties</strong> incentivizing external discovery</li>
626
+ <li><strong>Benchmark evaluation</strong> testing against standardized problem sets</li>
627
+ </ul>
628
+
629
+ <p>
630
+ Red teaming improves models but cannot find all problems. The attack surface is too large, and adversaries continue developing new techniques.
631
+ </p>
632
+
633
+ <h2>Responsible Deployment Practices</h2>
634
+
635
+ <p>
636
+ Beyond technical mitigations, responsible deployment requires organizational and procedural safeguards.
637
+ </p>
638
+
639
+ <h3>Human in the Loop Systems</h3>
640
+
641
+ <p>
642
+ For high stakes applications, human oversight remains essential:
643
+ </p>
644
+
645
+ <ul>
646
+ <li><strong>Review before action</strong> requiring human approval for consequential decisions</li>
647
+ <li><strong>Monitoring and auditing</strong> continuously checking system behavior</li>
648
+ <li><strong>Easy escalation paths</strong> making it simple to flag problems</li>
649
+ <li><strong>Clear accountability</strong> assigning human responsibility for outcomes</li>
650
+ </ul>
651
+
652
+ <h3>Appropriate Use Case Selection</h3>
653
+
654
+ <p>
655
+ Not every application is suitable for LLM deployment:
656
+ </p>
657
+
658
+ <p>
659
+ <strong>Higher risk applications</strong> include:
660
+ </p>
661
+
662
+ <ul>
663
+ <li>Medical diagnosis and treatment recommendations</li>
664
+ <li>Legal advice and judicial decision support</li>
665
+ <li>Financial trading and investment decisions</li>
666
+ <li>Hiring and employment decisions</li>
667
+ <li>Content moderation with serious consequences</li>
668
+ <li>Safety critical systems</li>
669
+ </ul>
670
+
671
+ <p>
672
+ <strong>Lower risk applications</strong> include:
673
+ </p>
674
+
675
+ <ul>
676
+ <li>Creative writing assistance</li>
677
+ <li>Code suggestions with developer review</li>
678
+ <li>Brainstorming and ideation</li>
679
+ <li>Summarization of non critical content</li>
680
+ <li>Entertainment and games</li>
681
+ </ul>
682
+
683
+ <p>
684
+ Risk assessment should consider not just the application but the user population, available safeguards, and consequences of failure.
685
+ </p>
686
+
687
+ <h3>Transparency and User Education</h3>
688
+
689
+ <p>
690
+ Users need to understand LLM limitations:
691
+ </p>
692
+
693
+ <ul>
694
+ <li><strong>Clear disclosure</strong> that they are interacting with AI</li>
695
+ <li><strong>Explicit limitation warnings</strong> about potential errors</li>
696
+ <li><strong>Guidance on verification</strong> and when to seek other sources</li>
697
+ <li><strong>Feedback mechanisms</strong> to report problems</li>
698
+ </ul>
699
+
700
+ <p>
701
+ Transparency does not eliminate harm but enables informed decision making.
702
+ </p>
703
+
704
+ <h3>Continuous Monitoring and Improvement</h3>
705
+
706
+ <p>
707
+ Deployment is not the end but the beginning of ongoing work:
708
+ </p>
709
+
710
+ <ul>
711
+ <li><strong>Logging and analysis</strong> of model behavior in production</li>
712
+ <li><strong>Incident response processes</strong> for handling discovered problems</li>
713
+ <li><strong>Regular model updates</strong> incorporating improvements</li>
714
+ <li><strong>Stakeholder feedback integration</strong> especially from affected communities</li>
715
+ </ul>
716
+
717
+ <h2>The Ethical Dimension</h2>
718
+
719
+ <p>
720
+ Beyond technical and procedural considerations, hallucinations and bias raise profound ethical questions.
721
+ </p>
722
+
723
+ <h3>Responsibility and Accountability</h3>
724
+
725
+ <p>
726
+ When AI systems cause harm, who bears responsibility?
727
+ </p>
728
+
729
+ <ul>
730
+ <li><strong>Model developers</strong> who created the system?</li>
731
+ <li><strong>Deploying organizations</strong> who chose to use it?</li>
732
+ <li><strong>Users</strong> who relied on it without verification?</li>
733
+ <li><strong>Society</strong> for allowing deployment without adequate safeguards?</li>
734
+ </ul>
735
+
736
+ <p>
737
+ Current legal frameworks were not designed for AI and often leave accountability unclear. This gap creates moral hazard, allowing harm without consequence.
738
+ </p>
739
+
740
+ <h3>Justice and Equity</h3>
741
+
742
+ <p>
743
+ Bias in AI systems raises fundamental justice concerns:
744
+ </p>
745
+
746
+ <ul>
747
+ <li>Is it just to deploy systems known to disadvantage certain groups?</li>
748
+ <li>What obligations exist to those harmed by biased outputs?</li>
749
+ <li>How should benefits and risks be distributed across populations?</li>
750
+ <li>Who gets to define what constitutes bias and what constitutes legitimate difference?</li>
751
+ </ul>
752
+
753
+ <p>
754
+ These questions cannot be answered purely technically. They require ethical reasoning and democratic deliberation.
755
+ </p>
756
+
757
+ <h3>Informed Consent and Autonomy</h3>
758
+
759
+ <p>
760
+ Users interacting with LLMs often do not understand the risks:
761
+ </p>
762
+
763
+ <ul>
764
+ <li>Can consent be meaningful without understanding of limitations?</li>
765
+ <li>What obligations exist to inform users of risks?</li>
766
+ <li>How do we protect vulnerable populations who cannot assess AI reliability?</li>
767
+ </ul>
768
+
769
+ <h3>The Speed vs. Safety Tradeoff</h3>
770
+
771
+ <p>
772
+ Commercial pressures push rapid deployment:
773
+ </p>
774
+
775
+ <ul>
776
+ <li>Competitive dynamics reward speed over safety</li>
777
+ <li>The costs of errors often fall on others</li>
778
+ <li>Slow, careful development loses market share</li>
779
+ <li>Regulatory frameworks lag technology</li>
780
+ </ul>
781
+
782
+ <blockquote>
783
+ "We are running one of the largest experiments in human history, deploying powerful AI systems to billions of people while still understanding little about their failure modes. The subjects of this experiment did not consent."
784
+ </blockquote>
785
+
786
+ <h2>Looking Forward</h2>
787
+
788
+ <p>
789
+ The future trajectory of hallucinations and bias in LLMs remains uncertain. Several possibilities exist.
790
+ </p>
791
+
792
+ <h3>Optimistic Scenarios</h3>
793
+
794
+ <p>
795
+ Technology might improve significantly:
796
+ </p>
797
+
798
+ <ul>
799
+ <li><strong>New architectures</strong> might inherently resist hallucination</li>
800
+ <li><strong>Better alignment techniques</strong> might genuinely improve reliability</li>
801
+ <li><strong>Hybrid systems</strong> combining LLMs with verification might achieve both capability and accuracy</li>
802
+ <li><strong>Improved training data</strong> might reduce bias at the source</li>
803
+ </ul>
804
+
805
+ <h3>Pessimistic Scenarios</h3>
806
+
807
+ <p>
808
+ Alternatively, problems might worsen:
809
+ </p>
810
+
811
+ <ul>
812
+ <li><strong>Scale without improvement</strong> as deployment expands faster than safety</li>
813
+ <li><strong>Training data degradation</strong> as AI generated content contaminates the web</li>
814
+ <li><strong>Adversarial arms races</strong> where attackers stay ahead of defenses</li>
815
+ <li><strong>Regulatory failure</strong> leaving markets to prioritize capability over safety</li>
816
+ </ul>
817
+
818
+ <h3>What Needs to Happen</h3>
819
+
820
+ <p>
821
+ Regardless of technical trajectory, societal responses matter:
822
+ </p>
823
+
824
+ <p>
825
+ <strong>Research investment</strong> in understanding and mitigating these problems must continue. This includes fundamental research on why models fail and applied research on practical solutions.
826
+ </p>
827
+
828
+ <p>
829
+ <strong>Regulatory frameworks</strong> need development. Appropriate regulation can align incentives, require transparency, and ensure accountability without stifling beneficial innovation.
830
+ </p>
831
+
832
+ <p>
833
+ <strong>Professional standards</strong> should emerge for responsible AI deployment. Professional communities in law, medicine, journalism, and other fields should develop norms for AI use.
834
+ </p>
835
+
836
+ <p>
837
+ <strong>Public education</strong> must help people understand AI capabilities and limitations. Media literacy for the AI age is essential.
838
+ </p>
839
+
840
+ <p>
841
+ <strong>Inclusive development</strong> processes should involve affected communities in AI design and governance. Those most impacted by bias should have voice in addressing it.
842
+ </p>
843
+
844
+ <h2>Conclusion</h2>
845
+
846
+ <p>
847
+ Hallucinations and bias are not bugs in large language models. They are <strong>fundamental characteristics</strong> that emerge from how these systems are built and trained. They cannot be fully eliminated with current approaches, only managed and mitigated.
848
+ </p>
849
+
850
+ <p>
851
+ The danger lies not just in the existence of these problems but in the <em>mismatch between capability and reliability</em>. LLMs are impressively capable, producing fluent, helpful, and often accurate outputs. This capability builds trust that their reliability does not fully warrant. Users, organizations, and societies are adopting these systems faster than we are solving their fundamental problems.
852
+ </p>
853
+
854
+ <p>
855
+ Responsible use of LLMs requires honest acknowledgment of limitations. It requires appropriate application choices, human oversight, continuous monitoring, and willingness to constrain deployment when risks outweigh benefits. It requires investment in safety research commensurate with investment in capability development.
856
+ </p>
857
+
858
+ <p>
859
+ Most fundamentally, it requires recognizing that deploying powerful AI systems to billions of people is not merely a technical project but a social and ethical one. The questions of who benefits, who bears risks, who decides, and who is accountable cannot be answered by algorithms. They require human judgment, democratic deliberation, and moral seriousness.
860
+ </p>
861
+
862
+ <p>
863
+ The golden age of AI offers tremendous potential for human benefit. Realizing that potential while avoiding serious harm requires taking hallucinations and bias not as problems to be dismissed or minimized but as fundamental challenges worthy of our most serious attention.
864
+ </p>
865
+
866
+ <p>
867
+ <strong>The technology is powerful. The question is whether we are wise enough to use it well.</strong>
868
+ </p>
post/llm limitations.md ADDED
@@ -0,0 +1,780 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ title: The Deeper You Understand AI, The More You Realize They Are Not As Smart As We Think
3
+ date: 2026-01-22
4
+ description: When you first interact with a modern AI assistant like ChatGPT, Claude, or Gemini, the experience can feel almost magical. The system understands your questions, provides thoughtful responses, remembers what you said earlier in the conversation, and seems to possess vast knowledge across countless domains. It feels like talking to an incredibly intelligent entity that truly comprehends you.
5
+ author: Hadad Darajat
6
+ tags:
7
+ - llm
8
+ - ai
9
+ - limitations
10
+ ---
11
+
12
+ <p>
13
+ When you first interact with a modern AI assistant like ChatGPT, Claude, or Gemini, the experience can feel almost magical. The system understands your questions, provides thoughtful responses, remembers what you said earlier in the conversation, and seems to possess vast knowledge across countless domains. It feels like talking to an incredibly intelligent entity that truly comprehends you.
14
+ </p>
15
+
16
+ <p>
17
+ But here is an uncomfortable truth that becomes increasingly apparent the more you work with these systems: <strong>the intelligence is largely an illusion</strong>. Behind the eloquent responses and seemingly thoughtful analysis lie fundamental limitations that reveal these systems are far less capable than they appear. The magic tricks have specific mechanics, and once you see them, you cannot unsee them.
18
+ </p>
19
+
20
+ <blockquote>
21
+ "The first time you use ChatGPT, you think it knows everything. The hundredth time, you realize it knows nothing, it just predicts what knowing something would sound like."
22
+ </blockquote>
23
+
24
+ <p>
25
+ This article explores the technical limitations that shatter the illusion of AI intelligence. Understanding these constraints is not about diminishing what AI can do, it is about developing realistic expectations that allow us to use these tools effectively while avoiding the pitfalls of overreliance and misplaced trust.
26
+ </p>
27
+
28
+ <h2>The Illusion of Understanding</h2>
29
+
30
+ <p>
31
+ Before diving into specific limitations, we need to address a fundamental misconception: <em>AI language models do not understand anything</em>. They do not think, reason, or comprehend in any meaningful sense. They perform extraordinarily sophisticated pattern matching and statistical prediction.
32
+ </p>
33
+
34
+ <p>
35
+ When you ask an AI a question, it does not ponder the meaning, consider implications, or draw on understanding. Instead, it calculates: <strong>"Given this input, what tokens are statistically most likely to follow?"</strong> The output sounds intelligent because it was trained on text produced by intelligent humans discussing topics intelligently.
36
+ </p>
37
+
38
+ <p>
39
+ This distinction matters because it explains every limitation we will discuss. The constraints are not temporary engineering problems that will be solved with the next update. They are consequences of what these systems fundamentally are.
40
+ </p>
41
+
42
+ <h3>The Chinese Room Revisited</h3>
43
+
44
+ <p>
45
+ Philosopher John Searle's famous <em>Chinese Room</em> thought experiment perfectly captures this distinction. Imagine a person in a room who receives Chinese characters through a slot, follows complex rules to manipulate those characters, and outputs responses. To outside observers, the room appears to understand Chinese. But the person inside understands nothing, they are just following rules.
46
+ </p>
47
+
48
+ <p>
49
+ Large language models are sophisticated Chinese Rooms. The rules are learned from training data rather than written by hand, and the processing happens at incredible speed and scale. But the fundamental nature is the same: symbol manipulation without understanding.
50
+ </p>
51
+
52
+ <blockquote>
53
+ "The model does not know what a cat is. It knows how humans write about cats, which patterns of words appear near the word cat, and what responses about cats tend to look like. This is not the same thing."
54
+ </blockquote>
55
+
56
+ <h2>Context Window: The Invisible Cage</h2>
57
+
58
+ <p>
59
+ Perhaps the most fundamental limitation of current AI systems is the <strong>context window</strong>, a fixed size buffer that determines how much information the model can consider at any moment. Think of it as the AI's working memory, except it is far more limited than you might imagine.
60
+ </p>
61
+
62
+ <h3>What Is a Context Window</h3>
63
+
64
+ <p>
65
+ The context window is measured in <em>tokens</em>, which are fragments of text that the model processes. A token is roughly three quarters of a word on average. The context window includes everything the model can see at once:
66
+ </p>
67
+
68
+ <ul>
69
+ <li>The system prompt setting up the AI's behavior</li>
70
+ <li>The entire conversation history</li>
71
+ <li>Any documents or data provided</li>
72
+ <li>The current question or instruction</li>
73
+ <li>The response being generated</li>
74
+ </ul>
75
+
76
+ <p>
77
+ Current context window sizes vary by model:
78
+ </p>
79
+
80
+ <ul>
81
+ <li><strong>GPT-3.5:</strong> 4,096 tokens (roughly 3,000 words)</li>
82
+ <li><strong>GPT-4:</strong> 8,192 tokens standard, 128,000 tokens extended</li>
83
+ <li><strong>Claude 3:</strong> 200,000 tokens (roughly 150,000 words)</li>
84
+ <li><strong>Gemini 1.5:</strong> Up to 1,000,000 tokens in some versions</li>
85
+ </ul>
86
+
87
+ <p>
88
+ These numbers might sound large, but consider what they mean in practice:
89
+ </p>
90
+
91
+ ```
92
+ Context Window Reality Check:
93
+
94
+ 4,096 tokens ≈ 3,000 words ≈ 6 pages of text
95
+ - A single long document can fill this entirely
96
+ - A moderately long conversation exhausts it
97
+ - Complex coding projects exceed it quickly
98
+
99
+ 128,000 tokens ≈ 96,000 words ≈ 192 pages
100
+ - Better, but still just a short book
101
+ - Large codebases still exceed this
102
+ - Extended conversations eventually hit limits
103
+
104
+ 200,000 tokens ≈ 150,000 words ≈ 300 pages
105
+ - Can handle a novel-length document
106
+ - But not multiple novels
107
+ - Still cannot hold your entire project
108
+ ```
109
+
110
+ <h3>The Sliding Window Problem</h3>
111
+
112
+ <p>
113
+ What happens when conversation length exceeds the context window? The oldest content gets pushed out. The model does not remember it, summarize it, or store it elsewhere. <strong>It simply vanishes.</strong>
114
+ </p>
115
+
116
+ <p>
117
+ Imagine having a conversation with someone who literally forgets everything you said more than ten minutes ago, but does so silently without telling you. That is what happens when context overflows.
118
+ </p>
119
+
120
+ ```
121
+ Conversation Timeline:
122
+
123
+ Message 1: "My name is Alex, I'm a software engineer."
124
+ Message 2: "I'm working on a Python project for healthcare."
125
+ Message 3: "The main challenge is HIPAA compliance."
126
+ ...
127
+ Message 50: [Context window fills up]
128
+ Message 51: [Message 1 falls out of context]
129
+ ...
130
+ Message 75: "What's my name again?"
131
+ AI Response: "I don't have information about your name
132
+ in our conversation."
133
+
134
+ The AI is not lying or being evasive. It genuinely
135
+ cannot access that information anymore.
136
+ ```
137
+
138
+ <p>
139
+ This creates bizarre situations where an AI that seemed to know you intimately suddenly has no idea who you are or what you have been discussing. The continuity was an illusion maintained only as long as the relevant information remained in the window.
140
+ </p>
141
+
142
+ <h3>Attention Degradation</h3>
143
+
144
+ <p>
145
+ Even within the context window, not all positions are treated equally. Research has demonstrated the <strong>"lost in the middle"</strong> phenomenon where models attend more strongly to information at the beginning and end of the context while effectively ignoring content in the middle.
146
+ </p>
147
+
148
+ <p>
149
+ This means that even if technically within the context window:
150
+ </p>
151
+
152
+ <ul>
153
+ <li>Information at the start of a long document may be processed well</li>
154
+ <li>Information at the end may be processed well</li>
155
+ <li>Information buried in the middle may be effectively invisible</li>
156
+ </ul>
157
+
158
+ <blockquote>
159
+ "A 200,000 token context window does not mean the model thoughtfully considers 200,000 tokens of information. It means it has access to that much text while paying meaningful attention to far less."
160
+ </blockquote>
161
+
162
+ <h2>Token Limits: The Hidden Walls</h2>
163
+
164
+ <p>
165
+ Beyond context windows, AI systems impose various <strong>token limits</strong> that further constrain their capabilities. These limits exist for technical, economic, and safety reasons.
166
+ </p>
167
+
168
+ <h3>Maximum Output Length</h3>
169
+
170
+ <p>
171
+ Every AI model has a maximum number of tokens it can generate in a single response. This is separate from the context window and often much smaller:
172
+ </p>
173
+
174
+ <ul>
175
+ <li><strong>GPT-4:</strong> 4,096 tokens maximum output</li>
176
+ <li><strong>Claude 3:</strong> 4,096 tokens typical, 8,192 with extended thinking</li>
177
+ <li><strong>Gemini:</strong> Varies by version, typically 2,048 to 8,192</li>
178
+ </ul>
179
+
180
+ <p>
181
+ This means even if a model has a 200,000 token context window, it can only respond with a few thousand tokens. Ask it to write a novel, and it will give you a chapter at most.
182
+ </p>
183
+
184
+ ```
185
+ User: "Write me a complete 50,000 word novel about space exploration."
186
+
187
+ Reality: The model can only output ~4,000 tokens (~3,000 words)
188
+
189
+ What happens:
190
+ - The model starts writing
191
+ - It reaches the output limit
192
+ - It stops, often mid-sentence or mid-chapter
193
+ - The "novel" is actually just the beginning
194
+
195
+ The model cannot plan around this limit. It does not think
196
+ "I have 4,000 tokens, so I should write a complete short
197
+ story instead." It just writes until it cannot write anymore.
198
+ ```
199
+
200
+ <h3>Truncation and Cutoffs</h3>
201
+
202
+ <p>
203
+ When you provide input that exceeds limits, different systems handle it differently, but none handle it well:
204
+ </p>
205
+
206
+ <ul>
207
+ <li><strong>Hard truncation:</strong> Content beyond the limit is simply cut off</li>
208
+ <li><strong>Error messages:</strong> The system refuses to process the input</li>
209
+ <li><strong>Silent truncation:</strong> Content is cut without notification</li>
210
+ <li><strong>Summarization attempts:</strong> Content is compressed, losing detail</li>
211
+ </ul>
212
+
213
+ <p>
214
+ Silent truncation is particularly dangerous because you may not realize the AI never saw crucial information:
215
+ </p>
216
+
217
+ ```
218
+ Your input: [Long legal document, 50,000 tokens]
219
+ + "Is there any liability issue on page 47?"
220
+
221
+ What gets processed: [First 30,000 tokens of document]
222
+ + Your question
223
+
224
+ What gets truncated: [Pages 35-62, including page 47]
225
+
226
+ AI Response: "I don't see any significant liability issues
227
+ in this document."
228
+
229
+ The response is technically true for what it saw.
230
+ But it never saw page 47 at all.
231
+ ```
232
+
233
+ <h3>Rate Limits and Throttling</h3>
234
+
235
+ <p>
236
+ Beyond per request limits, APIs impose rate limits that restrict how many requests you can make over time:
237
+ </p>
238
+
239
+ <ul>
240
+ <li><strong>Requests per minute:</strong> Often 3 to 60 depending on tier</li>
241
+ <li><strong>Tokens per minute:</strong> Limits total processing volume</li>
242
+ <li><strong>Tokens per day:</strong> Caps daily usage</li>
243
+ <li><strong>Concurrent requests:</strong> Limits simultaneous processing</li>
244
+ </ul>
245
+
246
+ <p>
247
+ These limits mean that even if you wanted to build a system that maintains context by repeatedly calling the API, you would quickly exhaust your quota.
248
+ </p>
249
+
250
+ <h2>Memory: The Grand Illusion</h2>
251
+
252
+ <p>
253
+ Perhaps the most misunderstood aspect of AI assistants is <strong>memory</strong>. Users often believe that AI systems remember them, learn from interactions, and build understanding over time. This belief is almost entirely false.
254
+ </p>
255
+
256
+ <h3>There Is No Memory</h3>
257
+
258
+ <p>
259
+ By default, large language models have <strong>no persistent memory whatsoever</strong>. Each API call is completely independent. The model does not remember:
260
+ </p>
261
+
262
+ <ul>
263
+ <li>Previous conversations</li>
264
+ <li>Your preferences or patterns</li>
265
+ <li>Corrections you made</li>
266
+ <li>Information you shared</li>
267
+ <li>That you exist at all</li>
268
+ </ul>
269
+
270
+ <p>
271
+ What appears to be memory within a conversation is simply the conversation history being included in the context window. The model reads the entire conversation fresh every time it responds. It does not remember your first message, it sees your first message in the context it was just provided.
272
+ </p>
273
+
274
+ ```python
275
+ # What users think happens:
276
+ user_message = "My favorite color is blue"
277
+ ai.remember(user=user_id, fact="favorite_color=blue") # Stored!
278
+ # Later...
279
+ ai.recall(user=user_id) # Retrieved!
280
+
281
+ # What actually happens:
282
+ messages = [
283
+ {"role": "user", "content": "My favorite color is blue"},
284
+ {"role": "assistant", "content": "Nice! Blue is a calming color."},
285
+ # ... more messages ...
286
+ {"role": "user", "content": "What's my favorite color?"}
287
+ ]
288
+
289
+ # The ENTIRE conversation is sent every single time
290
+ response = ai.generate(messages)
291
+
292
+ # If "favorite color is blue" scrolled out of context,
293
+ # the model has no idea what your favorite color is
294
+ ```
295
+
296
+ <h3>Simulated Memory Features</h3>
297
+
298
+ <p>
299
+ Some platforms have introduced "memory" features that create the illusion of persistence. These work through various mechanisms:
300
+ </p>
301
+
302
+ <p>
303
+ <strong>Explicit memory storage:</strong> The system extracts key facts and stores them in a database. These facts are injected into the system prompt for future conversations.
304
+ </p>
305
+
306
+ ```
307
+ System Prompt (invisible to user):
308
+ "The user's name is Alex. They are a software engineer.
309
+ They prefer concise responses. They work with Python.
310
+ They previously asked about machine learning basics."
311
+
312
+ + Actual conversation
313
+
314
+ This is not real memory. It is notes being read aloud
315
+ at the start of each conversation.
316
+ ```
317
+
318
+ <p>
319
+ <strong>Conversation summarization:</strong> Past conversations are summarized and compressed, then included in context. Detail is lost, but some continuity is preserved.
320
+ </p>
321
+
322
+ <p>
323
+ <strong>Vector database retrieval:</strong> Past interactions are embedded and stored. Relevant past content is retrieved and injected based on the current query.
324
+ </p>
325
+
326
+ <p>
327
+ All these approaches have significant limitations:
328
+ </p>
329
+
330
+ <ul>
331
+ <li>Storage is limited and selective</li>
332
+ <li>Retrieval may miss relevant information</li>
333
+ <li>Summarization loses nuance and detail</li>
334
+ <li>The model still has no actual memory, just augmented context</li>
335
+ <li>Privacy and security concerns arise from storing conversations</li>
336
+ </ul>
337
+
338
+ <h3>The Forgetting Problem</h3>
339
+
340
+ <p>
341
+ This architecture means AI systems exhibit bizarre forgetting patterns that no intelligent entity would:
342
+ </p>
343
+
344
+ <ul>
345
+ <li><strong>Sudden amnesia:</strong> Perfect recall one moment, complete ignorance the next when context shifts</li>
346
+ <li><strong>Inconsistent forgetting:</strong> Remembers obscure details while forgetting crucial context</li>
347
+ <li><strong>No degradation curve:</strong> Information does not fade gradually, it disappears entirely when pushed out</li>
348
+ <li><strong>No importance weighting:</strong> Cannot prioritize what to remember based on significance</li>
349
+ </ul>
350
+
351
+ <blockquote>
352
+ "If you had a human assistant who completely forgot your name every time you started a new conversation, you would question their competence. With AI, we accept this as normal because we do not realize it is happening."
353
+ </blockquote>
354
+
355
+ <h2>The Processing Paradox</h2>
356
+
357
+ <p>
358
+ AI models process text in ways that are profoundly different from human cognition, creating subtle but significant limitations.
359
+ </p>
360
+
361
+ <h3>Sequential Generation</h3>
362
+
363
+ <p>
364
+ LLMs generate text one token at a time, left to right, without the ability to plan ahead or revise. When a model writes a sentence, it:
365
+ </p>
366
+
367
+ <ol>
368
+ <li>Does not know how the sentence will end when it starts</li>
369
+ <li>Cannot go back and revise earlier tokens</li>
370
+ <li>Makes each token choice based only on preceding context</li>
371
+ <li>Has no internal drafting or planning process</li>
372
+ </ol>
373
+
374
+ <p>
375
+ This explains many failure modes:
376
+ </p>
377
+
378
+ ```
379
+ Why AI sometimes contradicts itself mid-response:
380
+
381
+ "The project deadline is flexible and can be extended...
382
+ however, the deadline is absolutely fixed and cannot change."
383
+
384
+ The model did not plan the response. It generated the first
385
+ clause, then based on that context, generated the second.
386
+ There was no moment of "wait, that contradicts what I just said."
387
+
388
+ Why AI struggles with complex logical arguments:
389
+
390
+ It cannot plan: "I need to establish premise A, then B,
391
+ then show how they combine to prove C."
392
+
393
+ It just generates text that sounds like logical arguments,
394
+ one token at a time, hoping the conclusion follows.
395
+ ```
396
+
397
+ <h3>Tokenization Artifacts</h3>
398
+
399
+ <p>
400
+ The way text is split into tokens creates unexpected limitations. Tokenization is not intuitive:
401
+ </p>
402
+
403
+ ```
404
+ Tokenization examples:
405
+ "Hello" → ["Hello"] (1 token)
406
+ "Pneumonoultramicroscopicsilicovolcanoconiosis" →
407
+ ["P", "ne", "um", "ono", "ult", "ram", "icro",
408
+ "scop", "ics", "il", "ico", "vol", "can", "oc",
409
+ "on", "iosis"] (many tokens)
410
+
411
+ "123" → ["123"] (1 token)
412
+ "12345" → ["123", "45"] (2 tokens)
413
+ "123456789" → ["123", "456", "789"] (3 tokens)
414
+
415
+ This affects:
416
+ - Character counting (often wrong)
417
+ - Letter manipulation (struggles with spelling)
418
+ - Arithmetic (inconsistent tokenization of numbers)
419
+ - Code formatting (tokens break mid-syntax)
420
+ ```
421
+
422
+ <p>
423
+ This is why AI systems:
424
+ </p>
425
+
426
+ <ul>
427
+ <li>Cannot reliably count characters or letters in words</li>
428
+ <li>Struggle with tasks like reversing strings</li>
429
+ <li>Make arithmetic errors on longer numbers</li>
430
+ <li>Have inconsistent handling of formatting and whitespace</li>
431
+ </ul>
432
+
433
+ <h3>No True Reasoning</h3>
434
+
435
+ <p>
436
+ What appears to be reasoning is pattern matching on examples of reasoning seen during training. The model does not:
437
+ </p>
438
+
439
+ <ul>
440
+ <li><strong>Maintain working memory</strong> for intermediate calculations</li>
441
+ <li><strong>Apply systematic algorithms</strong> it has learned</li>
442
+ <li><strong>Check its work</strong> or verify conclusions</li>
443
+ <li><strong>Recognize when it is confused</strong> or uncertain</li>
444
+ </ul>
445
+
446
+ ```
447
+ Ask: "What is 47 × 83?"
448
+
449
+ What humans do:
450
+ 1. Break into steps: 47 × 80 + 47 × 3
451
+ 2. Calculate 47 × 80 = 3,760
452
+ 3. Calculate 47 × 3 = 141
453
+ 4. Add: 3,760 + 141 = 3,901
454
+ 5. Optionally verify by alternative method
455
+
456
+ What LLMs do:
457
+ 1. "47 × 83" tokens activate patterns
458
+ 2. Predict next tokens based on similar problems in training
459
+ 3. Output something that looks like an answer
460
+ 4. If the exact problem was in training, answer is correct
461
+ 5. If not, answer might be plausible but wrong
462
+
463
+ The model is not computing. It is predicting what a
464
+ computation result would look like.
465
+ ```
466
+
467
+ <h2>Knowledge Limitations</h2>
468
+
469
+ <p>
470
+ The knowledge exhibited by AI systems is fundamentally different from human knowledge, with limitations that become apparent upon examination.
471
+ </p>
472
+
473
+ <h3>Training Data Cutoff</h3>
474
+
475
+ <p>
476
+ Every model has a <strong>knowledge cutoff date</strong> beyond which it knows nothing about the world:
477
+ </p>
478
+
479
+ <ul>
480
+ <li><strong>GPT-4:</strong> Training data up to April 2023</li>
481
+ <li><strong>Claude 3:</strong> Training data up to early 2024</li>
482
+ <li><strong>Gemini:</strong> Varies, some versions more recent</li>
483
+ </ul>
484
+
485
+ <p>
486
+ After the cutoff:
487
+ </p>
488
+
489
+ <ul>
490
+ <li>New events did not happen as far as the model knows</li>
491
+ <li>New scientific discoveries do not exist</li>
492
+ <li>New products were never released</li>
493
+ <li>Political changes, deaths, and births are unknown</li>
494
+ <li>Updated information remains outdated</li>
495
+ </ul>
496
+
497
+ ```
498
+ User (in 2025): "What do you think about [Major Event in Late 2024]?"
499
+
500
+ AI with April 2023 cutoff: "I don't have information about
501
+ that event. My knowledge was last updated in April 2023."
502
+
503
+ Or worse, if the AI hallucinates:
504
+ "[Completely fabricated response about an event it knows
505
+ nothing about, presented with full confidence]"
506
+ ```
507
+
508
+ <h3>Uneven Knowledge Distribution</h3>
509
+
510
+ <p>
511
+ Training data is not uniformly distributed. Models know vastly more about:
512
+ </p>
513
+
514
+ <ul>
515
+ <li><strong>English content</strong> compared to other languages</li>
516
+ <li><strong>Western perspectives</strong> compared to Global South</li>
517
+ <li><strong>Popular topics</strong> compared to niche subjects</li>
518
+ <li><strong>Recent decades</strong> compared to deep history</li>
519
+ <li><strong>Online culture</strong> compared to offline knowledge</li>
520
+ <li><strong>Technical fields</strong> with extensive documentation</li>
521
+ </ul>
522
+
523
+ <p>
524
+ This creates the illusion of comprehensive knowledge when the model is actually deeply uneven:
525
+ </p>
526
+
527
+ ```
528
+ Ask about Shakespeare: Extensive, detailed responses
529
+ Ask about a regional Indonesian poet: Sparse, possibly wrong
530
+
531
+ Ask about Silicon Valley startups: Rich information
532
+ Ask about African tech ecosystems: Surface level at best
533
+
534
+ Ask about mainstream medicine: Generally reliable
535
+ Ask about traditional medicine practices: Gaps and errors
536
+
537
+ The confidence level does not vary to match knowledge level.
538
+ The model speaks with equal authority about things it
539
+ knows well and things it barely knows.
540
+ ```
541
+
542
+ <h3>No Learning from Interactions</h3>
543
+
544
+ <p>
545
+ Perhaps most importantly, <strong>models do not learn from user interactions</strong>. When you:
546
+ </p>
547
+
548
+ <ul>
549
+ <li>Correct a mistake, the model does not update</li>
550
+ <li>Provide new information, it is not retained</li>
551
+ <li>Give feedback, it does not improve</li>
552
+ <li>Teach something, it does not learn</li>
553
+ </ul>
554
+
555
+ <p>
556
+ The same model that gave a wrong answer today will give the same wrong answer tomorrow. User interactions during deployment do not change model weights. Learning only happens during training, which users do not participate in.
557
+ </p>
558
+
559
+ <blockquote>
560
+ "Every conversation with an AI is Groundhog Day. No matter how much you teach it, tomorrow it wakes up knowing exactly what it knew before you started."
561
+ </blockquote>
562
+
563
+ <h2>Practical Implications</h2>
564
+
565
+ <p>
566
+ Understanding these limitations changes how we should interact with and rely upon AI systems.
567
+ </p>
568
+
569
+ <h3>For Individual Users</h3>
570
+
571
+ <p>
572
+ <strong>Never trust without verification.</strong> AI outputs should be treated as drafts, suggestions, or starting points, never as authoritative sources. Always verify:
573
+ </p>
574
+
575
+ <ul>
576
+ <li>Factual claims against reliable sources</li>
577
+ <li>Code by testing and review</li>
578
+ <li>Citations by actually checking them</li>
579
+ <li>Calculations by doing them yourself</li>
580
+ <li>Important information through multiple channels</li>
581
+ </ul>
582
+
583
+ <p>
584
+ <strong>Manage context actively.</strong> Do not assume the AI remembers earlier conversation. When context matters:
585
+ </p>
586
+
587
+ <ul>
588
+ <li>Repeat key information in important queries</li>
589
+ <li>Summarize relevant context before asking questions</li>
590
+ <li>Do not rely on information shared many messages ago</li>
591
+ <li>Start fresh conversations for new topics</li>
592
+ </ul>
593
+
594
+ <p>
595
+ <strong>Understand what you are getting.</strong> AI responses are:
596
+ </p>
597
+
598
+ <ul>
599
+ <li>Statistical predictions, not reasoned conclusions</li>
600
+ <li>Pattern matches, not original thoughts</li>
601
+ <li>Plausible text, not verified truth</li>
602
+ <li>Confident regardless of accuracy</li>
603
+ </ul>
604
+
605
+ <h3>For Developers and Organizations</h3>
606
+
607
+ <p>
608
+ <strong>Design for limitations.</strong> Build systems that account for AI constraints:
609
+ </p>
610
+
611
+ ```python
612
+ # Bad: Assuming unlimited context
613
+ def analyze_codebase(repo_path):
614
+ all_code = read_entire_repo(repo_path) # Could be millions of tokens
615
+ return ai.analyze(all_code) # Will fail or truncate
616
+
617
+ # Better: Working within limits
618
+ def analyze_codebase(repo_path):
619
+ files = get_all_files(repo_path)
620
+ summaries = []
621
+
622
+ for file in files:
623
+ # Analyze files individually within limits
624
+ if get_token_count(file) < MAX_CONTEXT:
625
+ summary = ai.analyze(file)
626
+ summaries.append(summary)
627
+ else:
628
+ # Split large files
629
+ chunks = split_into_chunks(file, MAX_CONTEXT)
630
+ for chunk in chunks:
631
+ summary = ai.analyze(chunk)
632
+ summaries.append(summary)
633
+
634
+ # Combine summaries, again respecting limits
635
+ return combine_summaries(summaries)
636
+ ```
637
+
638
+ <p>
639
+ <strong>Implement verification layers.</strong> Do not deploy AI outputs directly to users or systems without checks:
640
+ </p>
641
+
642
+ <ul>
643
+ <li>Automated fact checking where possible</li>
644
+ <li>Human review for high stakes outputs</li>
645
+ <li>Consistency checking across multiple generations</li>
646
+ <li>Confidence thresholds for automated decisions</li>
647
+ </ul>
648
+
649
+ <p>
650
+ <strong>Set appropriate expectations.</strong> Communicate limitations to users:
651
+ </p>
652
+
653
+ <ul>
654
+ <li>Disclose that AI is being used</li>
655
+ <li>Explain what the AI can and cannot do</li>
656
+ <li>Provide clear guidance on verification</li>
657
+ <li>Create easy paths for error reporting</li>
658
+ </ul>
659
+
660
+ <h3>For Decision Makers</h3>
661
+
662
+ <p>
663
+ <strong>Resist the hype.</strong> AI capabilities are impressive but limited:
664
+ </p>
665
+
666
+ <ul>
667
+ <li>Do not assume AI can replace human judgment</li>
668
+ <li>Do not deploy AI in high stakes situations without safeguards</li>
669
+ <li>Do not believe vendor claims without independent verification</li>
670
+ <li>Do not expect current limitations to disappear soon</li>
671
+ </ul>
672
+
673
+ <p>
674
+ <strong>Invest in understanding.</strong> Organizations using AI need:
675
+ </p>
676
+
677
+ <ul>
678
+ <li>Technical literacy among leadership</li>
679
+ <li>Realistic assessment of capabilities and risks</li>
680
+ <li>Ongoing monitoring of AI system behavior</li>
681
+ <li>Clear accountability for AI assisted decisions</li>
682
+ </ul>
683
+
684
+ <h2>The Deeper Truth</h2>
685
+
686
+ <p>
687
+ The limitations discussed in this article point to a deeper truth about current AI: <strong>these systems are sophisticated tools, not intelligent agents</strong>. They are immensely useful for many tasks, but they operate in ways fundamentally different from human cognition.
688
+ </p>
689
+
690
+ <p>
691
+ The appearance of intelligence emerges from:
692
+ </p>
693
+
694
+ <ul>
695
+ <li>Vast training data encoding human knowledge patterns</li>
696
+ <li>Sophisticated statistical modeling of language</li>
697
+ <li>Massive computational resources</li>
698
+ <li>Clever interface design that guides interactions</li>
699
+ <li>Human tendency to anthropomorphize</li>
700
+ </ul>
701
+
702
+ <p>
703
+ But beneath this appearance:
704
+ </p>
705
+
706
+ <ul>
707
+ <li>There is no understanding, only pattern matching</li>
708
+ <li>There is no memory, only context windows</li>
709
+ <li>There is no reasoning, only plausible text generation</li>
710
+ <li>There is no learning, only static trained weights</li>
711
+ <li>There is no knowledge, only statistical associations</li>
712
+ </ul>
713
+
714
+ <h3>Why This Matters</h3>
715
+
716
+ <p>
717
+ Understanding AI limitations is not about being pessimistic or dismissive. It is about <em>using these tools effectively</em>. A carpenter who understands that a saw cannot hammer nails uses both saw and hammer appropriately. A user who understands AI limitations can:
718
+ </p>
719
+
720
+ <ul>
721
+ <li>Choose appropriate use cases</li>
722
+ <li>Implement necessary safeguards</li>
723
+ <li>Avoid costly mistakes from overreliance</li>
724
+ <li>Get better results through informed interaction</li>
725
+ <li>Maintain realistic expectations</li>
726
+ </ul>
727
+
728
+ <blockquote>
729
+ "The danger is not that AI is too limited. The danger is that we do not recognize the limits until after we have trusted it with something important."
730
+ </blockquote>
731
+
732
+ <h2>Looking Forward</h2>
733
+
734
+ <p>
735
+ Will these limitations be overcome? Some may improve with future research:
736
+ </p>
737
+
738
+ <ul>
739
+ <li><strong>Context windows</strong> are expanding, though attention degradation persists</li>
740
+ <li><strong>Retrieval augmentation</strong> can extend effective knowledge access</li>
741
+ <li><strong>Chain of thought prompting</strong> improves some reasoning tasks</li>
742
+ <li><strong>Tool use</strong> allows models to perform actions they cannot do internally</li>
743
+ </ul>
744
+
745
+ <p>
746
+ However, some limitations appear more fundamental:
747
+ </p>
748
+
749
+ <ul>
750
+ <li>Statistical pattern matching may never equal true understanding</li>
751
+ <li>Training on text may never ground models in physical reality</li>
752
+ <li>Predicting tokens may never produce genuine reasoning</li>
753
+ <li>The absence of consciousness means no real comprehension</li>
754
+ </ul>
755
+
756
+ <p>
757
+ Future AI architectures may address these issues, but current transformer based LLMs have inherent constraints that engineering improvements alone cannot fully overcome.
758
+ </p>
759
+
760
+ <h2>Conclusion</h2>
761
+
762
+ <p>
763
+ The deeper you understand AI, the more you realize that the intelligence on display is a very convincing performance rather than genuine cognition. These systems excel at producing text that looks like it comes from an intelligent source because they learned from billions of examples of intelligent text. But the mechanism is fundamentally different from human thought.
764
+ </p>
765
+
766
+ <p>
767
+ Context windows impose hard limits on what the model can consider. Token limits constrain inputs and outputs. Memory is an illusion maintained only within conversation bounds. Knowledge is frozen at training time and unevenly distributed. Reasoning is simulated through pattern matching rather than executed through genuine logic.
768
+ </p>
769
+
770
+ <p>
771
+ None of this means AI is useless. These are remarkably capable tools that can genuinely augment human productivity when used appropriately. But <strong>appropriate use requires understanding limitations</strong>. The user who treats AI as an infallible oracle will eventually be burned. The user who treats it as a useful but flawed tool will extract tremendous value while avoiding the worst pitfalls.
772
+ </p>
773
+
774
+ <p>
775
+ The magic trick is impressive. But once you know how it works, you see it for what it is: a very sophisticated trick, not actual magic. And that knowledge makes you not a worse audience, but a better user.
776
+ </p>
777
+
778
+ <p>
779
+ <strong>The most important skill in the age of AI may be knowing exactly how limited AI really is.</strong>
780
+ </p>
post/mwb.md ADDED
@@ -0,0 +1,530 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ title: The Golden Era of Mobile Blogging with MyWapBlog
3
+ date: 2023-11-21
4
+ description: In the late 2000s, before the smartphone revolution transformed how we interact with the internet, there existed a vibrant ecosystem of mobile web platforms that catered to users accessing the internet through feature phones.
5
+ author: Hadad Darajat
6
+ tags:
7
+ - mywapblog
8
+ - mwb
9
+ ---
10
+
11
+ <p>
12
+ In the late 2000s, before the smartphone revolution transformed how we interact with the internet, there existed a vibrant ecosystem of mobile web platforms that catered to users accessing the internet through feature phones. Among these platforms, <strong>MyWapBlog.com</strong> stood out as a pioneer that democratized blogging for millions of users across the developing world, particularly in Indonesia, India, and other Southeast Asian countries.
13
+ </p>
14
+
15
+ <blockquote>
16
+ "MyWapBlog was not just a blogging platform. It was a cultural phenomenon that introduced an entire generation to content creation, web publishing, and online communities through devices that fit in their pockets."
17
+ </blockquote>
18
+
19
+ <h2>The Dawn of Mobile Blogging</h2>
20
+
21
+ <p>
22
+ The mid to late 2000s represented a unique moment in internet history. Desktop computers were expensive and not widely available in many developing countries. Internet cafes existed but charged by the hour. However, mobile phones were becoming increasingly affordable, and mobile internet access through <strong>GPRS</strong> and <strong>EDGE</strong> networks was expanding rapidly.
23
+ </p>
24
+
25
+ <p>
26
+ This created a perfect storm of opportunity. Millions of people had their first internet experience not through a computer screen, but through a <em>tiny 2.4 inch display</em> on a Nokia, Sony Ericsson, or Samsung feature phone. They needed platforms optimized for these constraints, and MyWapBlog emerged to fill that need.
27
+ </p>
28
+
29
+ <p>
30
+ MyWapBlog launched around 2007 and quickly gained traction because it understood its audience perfectly. The platform was built from the ground up for mobile browsers with these characteristics:
31
+ </p>
32
+
33
+ <ul>
34
+ <li><strong>Lightweight pages</strong> that loaded quickly even on slow GPRS connections</li>
35
+ <li><strong>WAP optimization</strong> using minimal HTML and compact code</li>
36
+ <li><strong>Simple navigation</strong> designed for numeric keypads and directional buttons</li>
37
+ <li><strong>Low bandwidth consumption</strong> crucial when data was expensive and limited</li>
38
+ <li><strong>No image heavy designs</strong> that would consume precious kilobytes</li>
39
+ </ul>
40
+
41
+ <h2>Why MyWapBlog Became a Phenomenon</h2>
42
+
43
+ <p>
44
+ Several factors contributed to MyWapBlog's explosive popularity during its heyday. Understanding these elements reveals why the platform resonated so deeply with its user base.
45
+ </p>
46
+
47
+ <h3>1. Accessibility and Zero Barrier to Entry</h3>
48
+
49
+ <p>
50
+ Creating a MyWapBlog account was remarkably simple. Users could register directly from their mobile phones in minutes. No email verification was strictly required in early versions, no complicated setup processes, and <em>absolutely no cost</em>. This was revolutionary for young people who wanted to express themselves online but lacked access to computers or the technical knowledge to set up traditional blogs.
51
+ </p>
52
+
53
+ <p>
54
+ The registration process looked something like this:
55
+ </p>
56
+
57
+ <ol>
58
+ <li>Navigate to mywapblog.com from your mobile browser</li>
59
+ <li>Click "Daftar" or "Register"</li>
60
+ <li>Enter username, password, and basic information</li>
61
+ <li>Choose a subdomain like username.mywapblog.com</li>
62
+ <li>Start posting immediately</li>
63
+ </ol>
64
+
65
+ <p>
66
+ Within five minutes, anyone with a basic feature phone could become a published blogger with their own corner of the internet.
67
+ </p>
68
+
69
+ <h3>2. The Social Features that Built Communities</h3>
70
+
71
+ <p>
72
+ MyWapBlog was not just about publishing content. It was fundamentally a <strong>social platform</strong> that fostered interaction and community building. Several features made this possible:
73
+ </p>
74
+
75
+ <p>
76
+ <strong>The Shoutbox</strong> was perhaps the most beloved feature. This was a simple widget placed on blog sidebars where visitors could leave quick messages. Unlike comments which were attached to specific posts, the shoutbox was a freeform chat area where conversations flowed continuously. It became the heart of social interaction, where bloggers and readers connected, flirted, argued, and built friendships.
77
+ </p>
78
+
79
+ <blockquote>
80
+ "The shoutbox was addictive. You would refresh your blog every few minutes just to see if someone left you a message. It was like primitive social media, and we loved it."
81
+ <br><em>- A nostalgic MyWapBlog user</em>
82
+ </blockquote>
83
+
84
+ <p>
85
+ Other social features included:
86
+ </p>
87
+
88
+ <ul>
89
+ <li><strong>Follow/Friend system</strong> to connect with other bloggers</li>
90
+ <li><strong>Blog directories</strong> categorized by topic and popularity</li>
91
+ <li><strong>Comments section</strong> for post specific discussions</li>
92
+ <li><strong>Private messaging</strong> between users</li>
93
+ <li><strong>Blog awards and badges</strong> for popular or active blogs</li>
94
+ <li><strong>Tag systems</strong> for content discovery</li>
95
+ </ul>
96
+
97
+ <h3>3. Customization and Personal Expression</h3>
98
+
99
+ <p>
100
+ Despite the technical constraints of mobile browsers, MyWapBlog offered surprising customization options. Users could personalize their blogs to reflect their personality and interests.
101
+ </p>
102
+
103
+ <p>
104
+ <em>Template customization</em> allowed users to choose from various pre-made designs or, for more advanced users, edit the HTML and CSS directly. This led to a vibrant ecosystem of template designers who would create and share custom designs. Some users even sold premium templates for small amounts of money, creating an early form of digital entrepreneurship.
105
+ </p>
106
+
107
+ <p>
108
+ Customization options included:
109
+ </p>
110
+
111
+ <ul>
112
+ <li>Color schemes and backgrounds</li>
113
+ <li>Font styles and sizes</li>
114
+ <li>Widget placement and configuration</li>
115
+ <li>Custom headers and footers</li>
116
+ <li>Background music using MIDI files (which was hugely popular)</li>
117
+ <li>Hit counters and visitor statistics</li>
118
+ </ul>
119
+
120
+ <p>
121
+ The ability to add <strong>background music</strong> deserves special mention. Blogs would automatically play MIDI versions of popular songs when visitors arrived. While this might seem annoying by today's standards, in the MyWapBlog era, it was a coveted feature that added personality and flair to your blog.
122
+ </p>
123
+
124
+ <h2>The Content Ecosystem</h2>
125
+
126
+ <p>
127
+ What did people actually blog about on MyWapBlog? The content was as diverse as the users themselves, creating a rich tapestry of teenage angst, creative writing, social commentary, and everyday life documentation.
128
+ </p>
129
+
130
+ <h3>Popular Content Categories</h3>
131
+
132
+ <p>
133
+ <strong>Personal Diaries and Life Updates</strong> dominated the platform. Users treated their blogs as digital diaries, sharing daily experiences, feelings, relationship drama, school problems, and family issues. The raw, unfiltered nature of this content created authentic connections between bloggers and readers.
134
+ </p>
135
+
136
+ <p>
137
+ <strong>Poetry and Creative Writing</strong> flourished on MyWapBlog. Aspiring poets would share their verses, often melancholic or romantic in nature. Short stories, song lyrics, and personal essays found enthusiastic audiences. The platform became an incubator for young Indonesian writers.
138
+ </p>
139
+
140
+ <p>
141
+ <strong>Quotes and Motivational Content</strong> were shared endlessly. Users would post their favorite quotes, create graphic text art using ASCII characters, and compile collections of wise sayings. These posts were highly shareable and helped blogs gain visibility.
142
+ </p>
143
+
144
+ <p>
145
+ <strong>Tutorial and Tech Content</strong> emerged as power users shared their knowledge. Tutorials covered topics like:
146
+ </p>
147
+
148
+ <ol>
149
+ <li>How to customize MyWapBlog templates</li>
150
+ <li>HTML and CSS basics for mobile</li>
151
+ <li>Creating custom widgets</li>
152
+ <li>Optimizing images for mobile viewing</li>
153
+ <li>Increasing blog traffic and followers</li>
154
+ <li>Java game downloads and mobile tricks</li>
155
+ </ol>
156
+
157
+ <p>
158
+ <strong>Entertainment Content</strong> including gossip about celebrities, music reviews, mobile game recommendations, and compilations of jokes or funny stories attracted large readerships.
159
+ </p>
160
+
161
+ <h3>The Writing Culture</h3>
162
+
163
+ <p>
164
+ MyWapBlog developed its own <em>linguistic and stylistic conventions</em>. The character limits and mobile typing constraints influenced how people wrote. Common patterns included:
165
+ </p>
166
+
167
+ <ul>
168
+ <li>Excessive use of emoticons and text faces like :) :D T_T ^_^</li>
169
+ <li>Creative spelling and abbreviations like "gw" (gue/aku), "lo" (lu/kamu), "yg" (yang)</li>
170
+ <li>Alay language mixing numbers and letters like "4ku" (aku), "k4mu" (kamu)</li>
171
+ <li>Excessive punctuation for emphasis like "!!!!!" or "????"</li>
172
+ <li>All caps for shouting or emphasis</li>
173
+ <li>Strategic use of line breaks due to small screen formatting</li>
174
+ </ul>
175
+
176
+ <p>
177
+ While purists criticized this as degrading language standards, it represented authentic youth culture and creative adaptation to technological constraints.
178
+ </p>
179
+
180
+ <h2>The Technical Infrastructure</h2>
181
+
182
+ <p>
183
+ From a technical perspective, MyWapBlog's architecture was impressive for its time. The platform had to balance functionality with the severe limitations of mobile browsers and networks in the late 2000s.
184
+ </p>
185
+
186
+ <h3>The Technology Stack</h3>
187
+
188
+ <p>
189
+ While the exact technology stack was not publicly documented, MyWapBlog likely used:
190
+ </p>
191
+
192
+ <ul>
193
+ <li><strong>PHP</strong> for server side processing and dynamic content generation</li>
194
+ <li><strong>MySQL</strong> for database management storing posts, users, and settings</li>
195
+ <li><strong>Minimal JavaScript</strong> since many mobile browsers had limited or no JS support</li>
196
+ <li><strong>XHTML Mobile Profile</strong> and <strong>WML</strong> for markup optimized for mobile devices</li>
197
+ <li><strong>Simple CSS</strong> for styling with careful attention to rendering on limited browsers</li>
198
+ </ul>
199
+
200
+ <p>
201
+ The platform had to be <em>incredibly efficient</em>. Pages needed to be under 10-20 KB ideally to load acceptably on GPRS connections. This meant:
202
+ </p>
203
+
204
+ ```html
205
+ <!-- Example of typical MyWapBlog page structure -->
206
+ <!DOCTYPE html PUBLIC "-//WAPFORUM//DTD XHTML Mobile 1.0//EN">
207
+ <html xmlns="http://www.w3.org/1999/xhtml">
208
+ <head>
209
+ <title>Blog Title</title>
210
+ <style type="text/css">
211
+ body { font-size: small; margin: 2px; }
212
+ a { color: blue; text-decoration: none; }
213
+ .post { margin-bottom: 5px; border-bottom: 1px solid #ccc; }
214
+ </style>
215
+ </head>
216
+ <body>
217
+ <div class="header">
218
+ <h1>My Blog</h1>
219
+ </div>
220
+
221
+ <div class="post">
222
+ <h2>Post Title</h2>
223
+ <p>Post content here...</p>
224
+ <small>Posted on: 12/05/2009</small>
225
+ </div>
226
+
227
+ <div class="shoutbox">
228
+ <h3>Shoutbox</h3>
229
+ <!-- Shoutbox messages -->
230
+ </div>
231
+
232
+ <div class="footer">
233
+ <a href="/">Home</a> | <a href="/archive">Archive</a>
234
+ </div>
235
+ </body>
236
+ </html>
237
+ ```
238
+
239
+ <h3>Performance Optimization Strategies</h3>
240
+
241
+ <p>
242
+ MyWapBlog employed several clever optimization techniques:
243
+ </p>
244
+
245
+ <ol>
246
+ <li><strong>Pagination</strong> showing only 5-10 posts per page to reduce load</li>
247
+ <li><strong>Image proxying</strong> compressing and resizing images automatically</li>
248
+ <li><strong>Aggressive caching</strong> storing rendered pages to reduce database queries</li>
249
+ <li><strong>Simplified markup</strong> using semantic HTML without excessive div nesting</li>
250
+ <li><strong>Inline CSS</strong> to avoid additional HTTP requests for stylesheets</li>
251
+ <li><strong>Text compression</strong> using gzip when supported by the mobile browser</li>
252
+ </ol>
253
+
254
+ <h2>The Community and Social Dynamics</h2>
255
+
256
+ <p>
257
+ MyWapBlog was more than a platform, it was a <strong>thriving community</strong> with its own culture, hierarchies, celebrities, and dramas.
258
+ </p>
259
+
260
+ <h3>The Rise of Micro Celebrities</h3>
261
+
262
+ <p>
263
+ Certain bloggers achieved celebrity status within the MyWapBlog ecosystem. These were users whose blogs attracted thousands of followers and whose posts would generate hundreds of comments. Their influence was significant within the community.
264
+ </p>
265
+
266
+ <p>
267
+ Popular bloggers typically exhibited some combination of:
268
+ </p>
269
+
270
+ <ul>
271
+ <li><strong>Consistent posting</strong> updating multiple times daily</li>
272
+ <li><strong>Engaging writing</strong> whether funny, dramatic, or insightful</li>
273
+ <li><strong>Active social interaction</strong> responding to comments and shoutbox messages</li>
274
+ <li><strong>Aesthetic appeal</strong> having beautifully customized blog designs</li>
275
+ <li><strong>Strategic networking</strong> collaborating with other popular bloggers</li>
276
+ </ul>
277
+
278
+ <h3>The Concept of Blogwalking</h3>
279
+
280
+ <p>
281
+ <em>Blogwalking</em> was a cultural practice unique to this era of Indonesian blogging. It referred to the act of systematically visiting other people's blogs, leaving comments or shoutbox messages, with the expectation that they would visit your blog in return.
282
+ </p>
283
+
284
+ <blockquote>
285
+ "Blogwalking was the SEO of MyWapBlog era. The more you visited others, the more visibility you gained. It was social networking through actual engagement, not algorithms."
286
+ </blockquote>
287
+
288
+ <p>
289
+ A typical blogwalking session might involve:
290
+ </p>
291
+
292
+ <ol>
293
+ <li>Opening the blog directory or popular blogs list</li>
294
+ <li>Visiting 20-30 different blogs</li>
295
+ <li>Leaving a shoutbox message like "Hai, salam kenal, ditunggu kunjungan baliknya ya!"</li>
296
+ <li>Waiting for return visits and reciprocal messages</li>
297
+ <li>Building a network of regular visitors</li>
298
+ </ol>
299
+
300
+ <h3>Drama and Conflicts</h3>
301
+
302
+ <p>
303
+ Like any social platform, MyWapBlog had its share of drama. Conflicts erupted over:
304
+ </p>
305
+
306
+ <ul>
307
+ <li><strong>Template theft</strong> when someone copied another blogger's custom design</li>
308
+ <li><strong>Content plagiarism</strong> posting someone else's writing as your own</li>
309
+ <li><strong>Relationship drama</strong> love triangles and breakups played out publicly</li>
310
+ <li><strong>Cyber bullying</strong> harsh comments or coordinated harassment</li>
311
+ <li><strong>Fake accounts</strong> impersonating popular bloggers</li>
312
+ </ul>
313
+
314
+ <p>
315
+ These conflicts were taken seriously by the community and could result in reputation damage, loss of followers, or in extreme cases, reporting to platform administrators.
316
+ </p>
317
+
318
+ <h2>The Business Model and Monetization</h2>
319
+
320
+ <p>
321
+ MyWapBlog operated as a free platform, raising questions about its business model and sustainability. The platform employed several monetization strategies:
322
+ </p>
323
+
324
+ <p>
325
+ <strong>Advertising</strong> was the primary revenue source. Banner ads and text ads appeared on blog pages, though they were kept minimal to maintain the lightweight nature of pages. The ads were typically for mobile content services, ringtones, games, and other mobile specific products popular in that era.
326
+ </p>
327
+
328
+ <p>
329
+ <strong>Premium features</strong> were offered for small fees. Users could pay to:
330
+ </p>
331
+
332
+ <ul>
333
+ <li>Remove ads from their blog</li>
334
+ <li>Use custom domains instead of subdomains</li>
335
+ <li>Access premium templates</li>
336
+ <li>Get increased storage for images</li>
337
+ <li>Unlock advanced customization options</li>
338
+ </ul>
339
+
340
+ <p>
341
+ The pricing was typically very affordable, around $1-3 per month, making it accessible to the target demographic.
342
+ </p>
343
+
344
+ <h2>The Decline and Fall</h2>
345
+
346
+ <p>
347
+ By the early 2010s, MyWapBlog's dominance began to wane. Several factors contributed to the platform's decline:
348
+ </p>
349
+
350
+ <h3>The Smartphone Revolution</h3>
351
+
352
+ <p>
353
+ The introduction of the iPhone in 2007 and Android phones shortly after began a revolution in mobile computing. By 2010-2011, smartphones were becoming more affordable and widespread. These devices had full web browsers that could access desktop websites comfortably.
354
+ </p>
355
+
356
+ <p>
357
+ Users no longer needed <em>mobile specific</em> platforms. They could use Blogger, WordPress, Tumblr, or other established blogging platforms directly from their phones. The WAP optimization that was MyWapBlog's strength became irrelevant.
358
+ </p>
359
+
360
+ <h3>The Rise of Social Media</h3>
361
+
362
+ <p>
363
+ Facebook became accessible via mobile and dominated social networking. Twitter, Instagram, and later platforms offered the immediacy and social interaction that MyWapBlog provided, but with larger networks and better mobile apps.
364
+ </p>
365
+
366
+ <p>
367
+ The quick status updates and photo sharing that defined social media made traditional blogging feel slow and outdated to many users. Why write a blog post when you could post a Facebook status and get immediate engagement?
368
+ </p>
369
+
370
+ <h3>Technical Limitations and Competition</h3>
371
+
372
+ <p>
373
+ MyWapBlog struggled to evolve with changing technology. The platform that was perfectly designed for feature phones was awkward on smartphones. Competitors who built mobile apps and responsive designs attracted users away.
374
+ </p>
375
+
376
+ <p>
377
+ Additionally, issues with:
378
+ </p>
379
+
380
+ <ul>
381
+ <li><strong>Spam and abuse</strong> overwhelming moderation capabilities</li>
382
+ <li><strong>Server stability</strong> struggling under high traffic loads</li>
383
+ <li><strong>Lack of innovation</strong> failing to add new features users wanted</li>
384
+ <li><strong>Security vulnerabilities</strong> leading to hacks and data concerns</li>
385
+ </ul>
386
+
387
+ <p>
388
+ By 2013-2014, MyWapBlog was a shadow of its former self. Many users had migrated to other platforms. The once vibrant community had fragmented and dispersed across the broader internet.
389
+ </p>
390
+
391
+ <h2>The Legacy and Cultural Impact</h2>
392
+
393
+ <p>
394
+ Despite its decline, MyWapBlog's impact on internet culture, particularly in Indonesia and Southeast Asia, should not be underestimated.
395
+ </p>
396
+
397
+ <h3>Democratizing Content Creation</h3>
398
+
399
+ <p>
400
+ MyWapBlog introduced <strong>millions of people</strong> to content creation and web publishing. For many users, particularly young people in developing countries, MyWapBlog was their first experience with:
401
+ </p>
402
+
403
+ <ul>
404
+ <li>Publishing content online</li>
405
+ <li>Building an audience</li>
406
+ <li>HTML and web design basics</li>
407
+ <li>Online community participation</li>
408
+ <li>Digital self expression</li>
409
+ </ul>
410
+
411
+ <p>
412
+ Many professional bloggers, web developers, content creators, and digital marketers today trace their origins back to tinkering with MyWapBlog templates and building followings on the platform.
413
+ </p>
414
+
415
+ <h3>Fostering Digital Literacy</h3>
416
+
417
+ <p>
418
+ The platform inadvertently served as an <em>educational tool</em>. Users learned valuable digital skills:
419
+ </p>
420
+
421
+ <ol>
422
+ <li><strong>Basic HTML and CSS</strong> through template customization</li>
423
+ <li><strong>Writing and communication</strong> through regular blogging</li>
424
+ <li><strong>Community management</strong> through moderating comments and interactions</li>
425
+ <li><strong>Digital etiquette</strong> understanding appropriate online behavior</li>
426
+ <li><strong>Content strategy</strong> learning what attracted readers and engagement</li>
427
+ </ol>
428
+
429
+ <h3>Cultural Documentation</h3>
430
+
431
+ <p>
432
+ MyWapBlog blogs serve as a <strong>time capsule</strong> of youth culture in the late 2000s and early 2010s. The posts, despite their sometimes cringeworthy nature, document authentic teenage experiences, social trends, linguistic evolution, and cultural shifts during a transformative period in digital history.
433
+ </p>
434
+
435
+ <blockquote>
436
+ "Reading my old MyWapBlog posts is embarrassing but also precious. It's a record of who I was at 15, what I cared about, how I expressed myself. That raw authenticity is something we've lost in the curated social media age."
437
+ <br><em>- Former MyWapBlog user reflecting in 2023</em>
438
+ </blockquote>
439
+
440
+ <h3>The Bridge Generation</h3>
441
+
442
+ <p>
443
+ MyWapBlog users were part of a <em>bridge generation</em> that experienced both pre and post smartphone internet. They remember typing blog posts on T9 keypads, they remember the joy of receiving shoutbox messages, and they remember the excitement of customizing templates with limited tools.
444
+ </p>
445
+
446
+ <p>
447
+ This generation developed a unique relationship with technology, appreciating both its possibilities and its limitations. They learned to be creative within constraints, a valuable skill that translates beyond blogging.
448
+ </p>
449
+
450
+ <h2>Lessons for Modern Platform Builders</h2>
451
+
452
+ <p>
453
+ MyWapBlog's rise and fall offer valuable lessons for anyone building digital platforms today:
454
+ </p>
455
+
456
+ <p>
457
+ <strong>Understand your users' constraints.</strong> MyWapBlog succeeded because it was built specifically for the limitations its users faced. It did not try to be a desktop experience on mobile, it embraced mobile's constraints and designed around them.
458
+ </p>
459
+
460
+ <p>
461
+ <strong>Community is more valuable than features.</strong> The technical features of MyWapBlog were relatively simple, but the community features like shoutboxes and blogwalking created strong user engagement and retention. People stayed for the connections, not the technology.
462
+ </p>
463
+
464
+ <p>
465
+ <strong>Lower barriers to entry.</strong> The easier you make it for users to start creating and participating, the larger your potential audience. MyWapBlog's five minute setup was key to its explosive growth.
466
+ </p>
467
+
468
+ <p>
469
+ <strong>Adapt or die.</strong> MyWapBlog's failure to evolve when technology shifted demonstrates the importance of continuous innovation. Success in one era does not guarantee survival in the next without adaptation.
470
+ </p>
471
+
472
+ <p>
473
+ <strong>Enable user creativity and ownership.</strong> Allowing users to customize templates, express themselves uniquely, and build personal brands within your platform creates stronger attachment and advocacy.
474
+ </p>
475
+
476
+ <h2>Nostalgia and Remembering MyWapBlog</h2>
477
+
478
+ <p>
479
+ Today, former MyWapBlog users occasionally reminisce about the platform on social media. Hashtags like <strong>#MyWapBlogMemories</strong> or <strong>#GenerasiMyWapBlog</strong> trend periodically as millennials share screenshots, stories, and memories.
480
+ </p>
481
+
482
+ <p>
483
+ The nostalgia is real and powerful because MyWapBlog represented more than just a blogging platform. It represented:
484
+ </p>
485
+
486
+ <ul>
487
+ <li><strong>Youth and innocence</strong> when internet drama felt significant</li>
488
+ <li><strong>Early internet culture</strong> before algorithms and monetization dominated</li>
489
+ <li><strong>Creative freedom</strong> experimenting without pressure to be perfect</li>
490
+ <li><strong>Authentic connection</strong> before social media became performative</li>
491
+ <li><strong>Technological wonder</strong> when mobile internet still felt magical</li>
492
+ </ul>
493
+
494
+ <p>
495
+ Some dedicated fans have even attempted to archive old MyWapBlog content or create spiritual successors to the platform, though none have recaptured the magic of the original.
496
+ </p>
497
+
498
+ <h2>Conclusion: The End of an Era</h2>
499
+
500
+ <p>
501
+ MyWapBlog represented a unique moment in internet history when mobile technology was powerful enough to enable content creation but limited enough to require specialized platforms. It democratized blogging for millions who would otherwise have been left out of the digital content revolution.
502
+ </p>
503
+
504
+ <p>
505
+ The platform taught an entire generation about <em>web publishing, digital communities, and online self expression</em>. It documented youth culture during a transformative period and created connections that transcended geographical boundaries.
506
+ </p>
507
+
508
+ <p>
509
+ While MyWapBlog itself has faded into internet history, its legacy lives on in the content creators, web developers, and digital professionals who got their start customizing templates and building audiences on the platform. It lives on in the collective memory of a generation who experienced the wonder of having their own corner of the internet accessible from a device in their pocket.
510
+ </p>
511
+
512
+ <blockquote>
513
+ "MyWapBlog was not perfect. The writing was often melodramatic, the designs were sometimes garish, and the technical limitations were real. But it was ours. It was authentic. It was the golden era of mobile blogging, and those of us who were there will never forget it."
514
+ </blockquote>
515
+
516
+ <p>
517
+ As we navigate the modern internet dominated by massive platforms, algorithm driven feeds, and performative content, there is something to be learned from the MyWapBlog era. The importance of community over scale, authenticity over polish, and accessibility over sophistication.
518
+ </p>
519
+
520
+ <p>
521
+ The golden era of MyWapBlog may be over, but its spirit, the belief that everyone deserves a voice and a platform to express themselves, remains as relevant today as it was when those first blogs loaded on tiny screens over painfully slow GPRS connections.
522
+ </p>
523
+
524
+ <p>
525
+ <strong>To all former MyWapBlog users:</strong> Your cringeworthy poetry, your dramatic diary entries, your carefully crafted shoutbox messages, they were all part of something special. You were pioneers of mobile content creation, and the internet is richer for your contributions, however small they may have seemed at the time.
526
+ </p>
527
+
528
+ <p>
529
+ <em>Salam blogwalking, wherever you are now.</em>
530
+ </p>
post/why the linux kernel uses c and not cpp.md ADDED
@@ -0,0 +1,227 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ title: Why the Linux Kernel Uses C and Not C++
3
+ date: 2024-03-21
4
+ description: The Linux kernel, one of the most successful open source projects in history, has been written predominantly in C since its inception in 1991. Despite the popularity and advancement of C++, the kernel development community has consistently rejected its adoption. This decision is not arbitrary but rooted in deep technical, philosophical, and practical considerations that define the very nature of operating system development.
5
+ author: Hadad Darajat
6
+ tags:
7
+ - linux
8
+ - linux_kernel
9
+ ---
10
+
11
+ <p>
12
+ The Linux kernel, one of the most successful open source projects in history, has been written predominantly in C since its inception in 1991. Despite the popularity and advancement of C++, the kernel development community has consistently rejected its adoption. This decision is not arbitrary but rooted in deep technical, philosophical, and practical considerations that define the very nature of operating system development.
13
+ </p>
14
+
15
+ <h2>Historical Context and Origins</h2>
16
+
17
+ <p>
18
+ When Linus Torvalds began working on Linux in 1991, he chose C as the implementation language. This choice was influenced by several factors. First, Unix, which Linux was inspired by, was rewritten in C by Dennis Ritchie and Ken Thompson in the early 1970s. This established C as the de facto language for systems programming. Second, C was well understood, had mature compilers, and provided the low level control necessary for kernel development.
19
+ </p>
20
+
21
+ <p>
22
+ At that time, C++ was still relatively young. Bjarne Stroustrup had created C++ in the early 1980s, and while it was gaining popularity in application development, it had not proven itself in the systems programming domain. The GNU C++ compiler was still evolving, and many of the features we consider standard in modern C++ were either experimental or nonexistent.
23
+ </p>
24
+
25
+ <p>
26
+ Linus Torvalds himself has been vocal about his distaste for C++. In a famous 2007 mailing list post, he stated that C++ leads to inefficient, bloated code and that limiting the kernel to C forces developers to think about their designs more carefully. This philosophical stance has shaped Linux development culture for decades.
27
+ </p>
28
+
29
+ <h2>The Philosophy of Simplicity</h2>
30
+
31
+ <p>
32
+ The Linux kernel adheres to a philosophy of simplicity and explicitness. C, being a relatively simple language with a small set of features, forces programmers to write straightforward code. There is no hiding behind abstractions or complex language features. What you see is what you get. This transparency is crucial when debugging kernel panics or tracking down subtle race conditions that could crash an entire system.
33
+ </p>
34
+
35
+ <p>
36
+ C++ introduces multiple paradigms including object oriented programming, template metaprogramming, and exception handling. While these features can be beneficial in application development, they add complexity that is undesirable in kernel space. The kernel must be predictable, deterministic, and absolutely reliable. Every abstraction layer introduces potential points of failure and makes reasoning about code behavior more difficult.
37
+ </p>
38
+
39
+ <p>
40
+ The KISS principle, Keep It Simple Stupid, is deeply embedded in kernel development culture. Simple code is easier to review, easier to audit for security vulnerabilities, and easier to maintain over the decades long lifecycle of operating system code. When thousands of developers worldwide contribute to a project, simplicity becomes not just a preference but a necessity.
41
+ </p>
42
+
43
+ <h2>Technical Advantages of C for Kernel Development</h2>
44
+
45
+ <p>
46
+ C provides direct access to memory and hardware without layers of abstraction. Kernel developers need to manipulate memory addresses, interact with hardware registers, and implement precise memory layouts for data structures. C allows this with minimal overhead. Pointer arithmetic, bit manipulation, and direct memory access are first class citizens in C, whereas C++ encourages higher level abstractions that can obscure what is actually happening at the hardware level.
47
+ </p>
48
+
49
+ <p>
50
+ The Linux kernel requires precise control over memory allocation. In kernel space, dynamic memory allocation can fail, and the code must handle these failures gracefully. C's simple malloc and free model, though manual and error prone, gives developers complete control. C++ constructors and destructors, automatic object lifetime management, and exception based error handling assume a level of runtime support that does not exist in kernel space.
51
+ </p>
52
+
53
+ <p>
54
+ Binary compatibility and ABI stability are critical concerns for the kernel. The kernel must maintain a stable interface with userspace programs and with loadable kernel modules. C has a simple, well defined ABI that has remained stable for decades. C++ name mangling, virtual function tables, and template instantiation create complex ABIs that vary between compiler versions and can break compatibility unexpectedly.
55
+ </p>
56
+
57
+ <h2>The Problem with C++ Features in Kernel Context</h2>
58
+
59
+ <p>
60
+ Exception handling in C++ relies on stack unwinding and runtime support that requires significant infrastructure. The kernel cannot afford the overhead of maintaining exception handling metadata. Moreover, exceptions can make control flow unpredictable. In kernel code, especially in interrupt handlers or when holding locks, you need to know exactly what code paths will execute. Exceptions that can jump arbitrarily up the call stack are incompatible with this requirement.
61
+ </p>
62
+
63
+ <p>
64
+ Virtual functions and runtime polymorphism introduce indirection through vtables. While the performance cost might be acceptable in userspace applications, in performance critical kernel code paths that execute millions of times per second, even small overheads matter. Furthermore, the indirection makes it harder to predict cache behavior and to optimize hot code paths.
65
+ </p>
66
+
67
+ <p>
68
+ Templates in C++ can generate enormous amounts of code through instantiation. This code bloat is problematic for the kernel, which must fit within memory constraints and maintain a small cache footprint. While templates can be used carefully, their complexity and potential for abuse make them dangerous in a large, collaborative project where not all contributors have deep C++ expertise.
69
+ </p>
70
+
71
+ <p>
72
+ The Standard Template Library and other C++ standard library components assume the existence of a standard library runtime. The kernel cannot link against libstdc++ or any standard library. It must be entirely self contained. While it is theoretically possible to use C++ without the standard library, doing so eliminates many of the perceived benefits of using C++ in the first place.
73
+ </p>
74
+
75
+ <h2>Code Comparison and Practical Differences</h2>
76
+
77
+ <p>
78
+ Consider a simple example of a linked list implementation. In the Linux kernel, lists are implemented using intrusive data structures where the list pointers are embedded directly in the data structure being listed.
79
+ </p>
80
+
81
+ <p>C kernel style linked list :</p>
82
+
83
+ ```c
84
+ struct list_head {
85
+ struct list_head *next;
86
+ struct list_head *prev;
87
+ };
88
+
89
+ struct task_struct {
90
+ pid_t pid;
91
+ char comm[16];
92
+ struct list_head tasks;
93
+ };
94
+
95
+ void add_task(struct list_head *head, struct task_struct *task)
96
+ {
97
+ task->tasks.next = head->next;
98
+ task->tasks.prev = head;
99
+ head->next->prev = &task->tasks;
100
+ head->next = &task->tasks;
101
+ }
102
+ ```
103
+
104
+ <p>
105
+ This approach provides zero overhead abstraction. There are no hidden allocations, no virtual function calls, and the memory layout is completely explicit. The compiler can inline everything and optimize aggressively.
106
+ </p>
107
+
108
+ <p>A C++ approach might look like this :</p>
109
+
110
+ ```cpp
111
+ template<typename T>
112
+ class List {
113
+ private:
114
+ struct Node {
115
+ T data;
116
+ Node* next;
117
+ Node* prev;
118
+ };
119
+ Node* head;
120
+ public:
121
+ void add(const T& item) {
122
+ Node* node = new Node{item, head->next, head};
123
+ head->next->prev = node;
124
+ head->next = node;
125
+ }
126
+ };
127
+ ```
128
+
129
+ <p>
130
+ While more elegant and type safe, this version requires dynamic allocation for nodes, uses templates that can bloat code size, and hides the memory layout behind abstractions. In kernel space, the allocation could fail, and there is no exception mechanism to handle it. The type safety is nice, but the kernel already has strict coding standards and review processes that catch type errors.
131
+ </p>
132
+
133
+ <h2>The Dangers and Risks</h2>
134
+
135
+ <p>
136
+ Allowing C++ in the kernel would open the door to misuse of complex features. With thousands of contributors of varying skill levels, enforcing a safe subset of C++ would be nearly impossible. Even experienced C++ developers can write code with subtle bugs involving object lifetime, initialization order, or template specialization. In kernel space, such bugs can cause system crashes, data corruption, or security vulnerabilities.
137
+ </p>
138
+
139
+ <p>
140
+ The implicit behavior of C++ is particularly dangerous in kernel context. Constructors and destructors run automatically, but in the kernel, you need to know exactly when resources are acquired and released. Automatic storage duration objects that call destructors when going out of scope can be problematic when you need to hold locks across multiple functions or when you need to guarantee that cleanup happens even if an error occurs.
141
+ </p>
142
+
143
+ <p>
144
+ Global constructors, which run before main in C++ programs, have no well defined initialization order across translation units. In kernel code that must initialize hardware in a specific sequence, this non determinism is unacceptable. The kernel uses explicit initialization phases and carefully controls the order in which subsystems start up.
145
+ </p>
146
+
147
+ <p>
148
+ Multiple inheritance and the diamond problem can create complex object layouts and ambiguous member access. While modern C++ has tools to manage this, the complexity is simply not worth the risk in kernel code where simplicity and predictability are paramount.
149
+ </p>
150
+
151
+ <h2>Performance Considerations</h2>
152
+
153
+ <p>
154
+ While well written C++ can be as fast as C, achieving this requires discipline and deep understanding of what the compiler generates. In the kernel, performance is not just about algorithmic complexity but about cache efficiency, branch prediction, and minimizing instruction count in hot paths. C's simplicity makes it easier to reason about performance and to write code that compiles to exactly the assembly you intend.
155
+ </p>
156
+
157
+ <p>
158
+ The kernel makes extensive use of likely and unlikely macros to give branch prediction hints to the CPU. It uses compiler barriers and memory barriers to control optimization and enforce memory ordering. These low level optimizations are straightforward in C but can interact unpredictably with C++ features like constructors or template instantiation.
159
+ </p>
160
+
161
+ <p>
162
+ Inline assembly, which the kernel uses extensively for architecture specific code, is more straightforward to integrate with C. C++ name mangling and calling conventions can complicate the interface between C++ and assembly code.
163
+ </p>
164
+
165
+ <h2>Maintainability and Long Term Stability</h2>
166
+
167
+ <p>
168
+ The Linux kernel is not a short lived project. Code written in the 1990s still runs today. This longevity requires stability not just in APIs but in the tools and language used to build the kernel. C has been remarkably stable. A C compiler from 1999 can still build much of the kernel with minimal changes. C++ has evolved significantly over the same period, with C++11, C++14, C++17, and C++20 each introducing substantial new features.
169
+ </p>
170
+
171
+ <p>
172
+ Adopting C++ would tie the kernel to a specific version of the language and require decisions about which features to allow. These decisions would need to be revisited as the language evolves, creating ongoing maintenance burden. By sticking with C, the kernel avoids this complexity.
173
+ </p>
174
+
175
+ <p>
176
+ Code review is also simpler with C. Reviewers do not need to understand template metaprogramming, SFINAE, or perfect forwarding. They need to understand C, which, while requiring careful attention to memory management and undefined behavior, is a smaller and more stable knowledge domain.
177
+ </p>
178
+
179
+ <h2>Cultural and Community Factors</h2>
180
+
181
+ <p>
182
+ The Linux kernel development community has built up decades of expertise, coding conventions, and tools around C. Changing languages would invalidate much of this institutional knowledge. Static analysis tools, debugging tools, and development workflows are all optimized for C. Introducing C++ would require rebuilding this entire ecosystem.
183
+ </p>
184
+
185
+ <p>
186
+ The kernel coding style is deeply ingrained in the community. The use of goto for error handling, the preference for short functions, the specific indentation style, all of these reflect a C centric worldview. C++ would encourage different patterns that could fragment the codebase and make it harder to maintain consistency.
187
+ </p>
188
+
189
+ <p>
190
+ Moreover, Linus Torvalds' strong opinions on language choice carry significant weight. As the original author and final arbiter of what goes into the kernel, his preference for C shapes the project's direction. While the kernel is collaborative, it is not a democracy, and major architectural decisions ultimately require his approval.
191
+ </p>
192
+
193
+ <h2>The Middle Ground and Rust</h2>
194
+
195
+ <p>
196
+ Interestingly, while C++ has been consistently rejected, the kernel community has recently begun experimenting with Rust. Rust offers memory safety guarantees that C lacks while maintaining low level control and zero cost abstractions. Unlike C++, Rust was designed with systems programming in mind from the start.
197
+ </p>
198
+
199
+ <p>
200
+ Rust's ownership system prevents entire classes of bugs at compile time without runtime overhead. It has no garbage collection, no required runtime, and generates efficient machine code. The kernel's adoption of Rust for certain drivers and subsystems suggests that the objection to C++ is not about avoiding modern languages but about choosing the right tool for the job.
201
+ </p>
202
+
203
+ <p>
204
+ This development reinforces that C++ specifically, not just any language beyond C, is seen as unsuitable. Rust addresses many of the concerns about C's unsafety without introducing the complexity and overhead that make C++ problematic for kernel development.
205
+ </p>
206
+
207
+ <h2>Conclusion</h2>
208
+
209
+ <p>
210
+ The Linux kernel's commitment to C is not merely tradition or stubbornness. It reflects a carefully considered technical decision based on the unique requirements of operating system development. The kernel needs predictability, performance, simplicity, and complete control over hardware. C provides all of these with minimal overhead and complexity.
211
+ </p>
212
+
213
+ <p>
214
+ C++ offers powerful abstractions and modern language features, but these come at a cost that is unacceptable in kernel space. The complexity of the language, the runtime requirements of many features, the ABI instability, and the potential for abuse all make C++ a poor fit for this domain.
215
+ </p>
216
+
217
+ <p>
218
+ Kernel development is fundamentally different from application development. The constraints are tighter, the consequences of bugs are more severe, and the need for low level control is absolute. C, despite its age and limitations, remains the right tool for this job. The kernel's success over more than three decades validates this choice.
219
+ </p>
220
+
221
+ <p>
222
+ As programming languages continue to evolve, the kernel community will undoubtedly continue to evaluate new options. But any language that hopes to supplement or replace C in the kernel must demonstrate that it can meet the same stringent requirements while offering concrete benefits. So far, only Rust has begun to make that case, and even then, it is being introduced cautiously and incrementally. C++ simply does not offer a compelling enough value proposition to justify the costs and risks of adoption.
223
+ </p>
224
+
225
+ <p>
226
+ For developers learning systems programming, understanding why C remains dominant in the kernel provides valuable insights into the tradeoffs between abstraction and control, between elegance and simplicity, and between modern language features and practical engineering constraints. The kernel's commitment to C is a masterclass in choosing the right tool for the job, even when that tool is not the newest or most fashionable option available.
227
+ </p>
public/assets/images/favicon.ico ADDED
public/assets/images/profile.png ADDED

Git LFS Details

  • SHA256: 0664c13c5f7a924faec265bf8673310e0a4bb19cdac10daf5fc42c8bab7df4c5
  • Pointer size: 131 Bytes
  • Size of remote file: 149 kB
src/client/App.tsx ADDED
@@ -0,0 +1,22 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ //
2
+ // SPDX-FileCopyrightText: Hadad <hadad@linuxmail.org>
3
+ // SPDX-License-Identifier: Apache-2.0
4
+ //
5
+
6
+ import { BrowserRouter, Routes, Route } from "react-router-dom";
7
+ import { Layout } from "./components/layout/Layout";
8
+ import { HomePage } from "./pages/HomePage";
9
+ import { PostPage } from "./pages/PostPage";
10
+
11
+ export const App = (): JSX.Element => {
12
+ return (
13
+ <BrowserRouter>
14
+ <Layout>
15
+ <Routes>
16
+ <Route path="/" element={<HomePage />} />
17
+ <Route path="/post/:slug" element={<PostPage />} />
18
+ </Routes>
19
+ </Layout>
20
+ </BrowserRouter>
21
+ );
22
+ };
src/client/components/blog/PostCard.tsx ADDED
@@ -0,0 +1,98 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ //
2
+ // SPDX-FileCopyrightText: Hadad <hadad@linuxmail.org>
3
+ // SPDX-License-Identifier: Apache-2.0
4
+ //
5
+
6
+ import { Link } from "react-router-dom";
7
+ import { Calendar, User, ArrowRight } from "lucide-react";
8
+ import { siteConfig } from "@shared/config";
9
+ import type { PostSummary } from "@shared/types";
10
+ import type { CSSProperties } from "react";
11
+
12
+ interface PostCardProps {
13
+ post: PostSummary;
14
+ }
15
+
16
+ const cardStyle: CSSProperties = {
17
+ display: "block",
18
+ backgroundColor: "var(--color-surface)",
19
+ borderRadius: "var(--border-radius-lg)",
20
+ padding: "var(--spacing-lg)",
21
+ border: "1px solid var(--color-border)",
22
+ textDecoration: "none",
23
+ transition:
24
+ "transform var(--transition-fast), box-shadow var(--transition-fast)",
25
+ };
26
+
27
+ const titleStyle: CSSProperties = {
28
+ fontSize: "var(--font-size-xl)",
29
+ fontWeight: 600,
30
+ color: "var(--color-text-primary)",
31
+ marginBottom: "var(--spacing-sm)",
32
+ lineHeight: 1.3,
33
+ };
34
+
35
+ const descriptionStyle: CSSProperties = {
36
+ fontSize: "var(--font-size-base)",
37
+ color: "var(--color-text-secondary)",
38
+ marginBottom: "var(--spacing-md)",
39
+ lineHeight: 1.5,
40
+ display: "-webkit-box",
41
+ WebkitLineClamp: 3,
42
+ WebkitBoxOrient: "vertical",
43
+ overflow: "hidden",
44
+ };
45
+
46
+ const metaContainerStyle: CSSProperties = {
47
+ display: "flex",
48
+ flexWrap: "wrap",
49
+ gap: "var(--spacing-md)",
50
+ alignItems: "center",
51
+ fontSize: "var(--font-size-sm)",
52
+ color: "var(--color-text-muted)",
53
+ };
54
+
55
+ const metaItemStyle: CSSProperties = {
56
+ display: "flex",
57
+ alignItems: "center",
58
+ gap: "var(--spacing-xs)",
59
+ };
60
+
61
+ const readMoreStyle: CSSProperties = {
62
+ display: "flex",
63
+ alignItems: "center",
64
+ gap: "var(--spacing-xs)",
65
+ color: "var(--color-accent)",
66
+ marginLeft: "auto",
67
+ fontWeight: 500,
68
+ };
69
+
70
+ const formatDate = (dateString: string): string => {
71
+ const date = new Date(dateString);
72
+ return date.toLocaleDateString(siteConfig.locale, siteConfig.dateFormat);
73
+ };
74
+
75
+ export const PostCard = ({ post }: PostCardProps): JSX.Element => {
76
+ return (
77
+ <Link to={`/post/${post.slug}`} style={cardStyle}>
78
+ <h2 style={titleStyle}>{post.frontMatter.title}</h2>
79
+ <p style={descriptionStyle}>{post.frontMatter.description}</p>
80
+ <div style={metaContainerStyle}>
81
+ <span style={metaItemStyle}>
82
+ <Calendar size={14} />
83
+ {formatDate(post.frontMatter.date)}
84
+ </span>
85
+ {post.frontMatter.author && (
86
+ <span style={metaItemStyle}>
87
+ <User size={14} />
88
+ {post.frontMatter.author}
89
+ </span>
90
+ )}
91
+ <span style={readMoreStyle}>
92
+ {siteConfig.messages.readMore}
93
+ <ArrowRight size={14} />
94
+ </span>
95
+ </div>
96
+ </Link>
97
+ );
98
+ };
src/client/components/blog/PostContent.tsx ADDED
@@ -0,0 +1,131 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ //
2
+ // SPDX-FileCopyrightText: Hadad <hadad@linuxmail.org>
3
+ // SPDX-License-Identifier: Apache-2.0
4
+ //
5
+
6
+ import { Link } from "react-router-dom";
7
+ import { Calendar, User, ArrowLeft, Tag } from "lucide-react";
8
+ import { siteConfig } from "@shared/config";
9
+ import type { Post } from "@shared/types";
10
+ import type { CSSProperties } from "react";
11
+
12
+ interface PostContentProps {
13
+ post: Post;
14
+ }
15
+
16
+ const articleStyle: CSSProperties = {
17
+ maxWidth: "var(--max-width-content)",
18
+ margin: "0 auto",
19
+ };
20
+
21
+ const backLinkStyle: CSSProperties = {
22
+ display: "inline-flex",
23
+ alignItems: "center",
24
+ gap: "var(--spacing-xs)",
25
+ color: "var(--color-accent)",
26
+ fontSize: "var(--font-size-sm)",
27
+ marginBottom: "var(--spacing-lg)",
28
+ textDecoration: "none",
29
+ };
30
+
31
+ const headerStyle: CSSProperties = {
32
+ marginBottom: "var(--spacing-xl)",
33
+ };
34
+
35
+ const titleStyle: CSSProperties = {
36
+ fontSize: "var(--font-size-4xl)",
37
+ fontWeight: 700,
38
+ color: "var(--color-text-primary)",
39
+ marginBottom: "var(--spacing-md)",
40
+ lineHeight: 1.2,
41
+ };
42
+
43
+ const metaContainerStyle: CSSProperties = {
44
+ display: "flex",
45
+ flexWrap: "wrap",
46
+ gap: "var(--spacing-md)",
47
+ alignItems: "center",
48
+ fontSize: "var(--font-size-sm)",
49
+ color: "var(--color-text-muted)",
50
+ marginBottom: "var(--spacing-md)",
51
+ };
52
+
53
+ const metaItemStyle: CSSProperties = {
54
+ display: "flex",
55
+ alignItems: "center",
56
+ gap: "var(--spacing-xs)",
57
+ };
58
+
59
+ const tagsContainerStyle: CSSProperties = {
60
+ display: "flex",
61
+ flexWrap: "wrap",
62
+ gap: "var(--spacing-xs)",
63
+ };
64
+
65
+ const tagStyle: CSSProperties = {
66
+ display: "inline-flex",
67
+ alignItems: "center",
68
+ gap: "2px",
69
+ backgroundColor: "var(--color-surface)",
70
+ color: "var(--color-text-secondary)",
71
+ padding: "var(--spacing-xs) var(--spacing-sm)",
72
+ borderRadius: "var(--border-radius-sm)",
73
+ fontSize: "var(--font-size-xs)",
74
+ border: "1px solid var(--color-border)",
75
+ };
76
+
77
+ const contentStyle: CSSProperties = {
78
+ lineHeight: 1.8,
79
+ color: "var(--color-text-primary)",
80
+ };
81
+
82
+ const formatDate = (dateString: string): string => {
83
+ const date = new Date(dateString);
84
+ return date.toLocaleDateString(siteConfig.locale, siteConfig.dateFormat);
85
+ };
86
+
87
+ export const PostContent = ({ post }: PostContentProps): JSX.Element => {
88
+ return (
89
+ <article style={articleStyle}>
90
+ <Link to="/" style={backLinkStyle}>
91
+ <ArrowLeft size={16} />
92
+ {siteConfig.messages.backToHome}
93
+ </Link>
94
+
95
+ <header style={headerStyle}>
96
+ <h1 style={titleStyle}>{post.frontMatter.title}</h1>
97
+
98
+ <div style={metaContainerStyle}>
99
+ <span style={metaItemStyle}>
100
+ <Calendar size={14} />
101
+ {formatDate(post.frontMatter.date)}
102
+ </span>
103
+ {post.frontMatter.author && (
104
+ <span style={metaItemStyle}>
105
+ <User size={14} />
106
+ {post.frontMatter.author}
107
+ </span>
108
+ )}
109
+ </div>
110
+
111
+ {post.frontMatter.tags && post.frontMatter.tags.length > 0 && (
112
+ <div style={tagsContainerStyle}>
113
+ {post.frontMatter.tags.map(
114
+ (tag: string): JSX.Element => (
115
+ <span key={tag} style={tagStyle}>
116
+ <Tag size={10} />
117
+ {tag}
118
+ </span>
119
+ )
120
+ )}
121
+ </div>
122
+ )}
123
+ </header>
124
+
125
+ <div
126
+ style={contentStyle}
127
+ dangerouslySetInnerHTML={{ __html: post.content }}
128
+ />
129
+ </article>
130
+ );
131
+ };
src/client/components/blog/PostList.tsx ADDED
@@ -0,0 +1,42 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ //
2
+ // SPDX-FileCopyrightText: Hadad <hadad@linuxmail.org>
3
+ // SPDX-License-Identifier: Apache-2.0
4
+ //
5
+
6
+ import { PostCard } from "./PostCard";
7
+ import { siteConfig } from "@shared/config";
8
+ import type { PostSummary } from "@shared/types";
9
+ import type { CSSProperties } from "react";
10
+
11
+ interface PostListProps {
12
+ posts: PostSummary[];
13
+ }
14
+
15
+ const listStyle: CSSProperties = {
16
+ display: "flex",
17
+ flexDirection: "column",
18
+ gap: "var(--spacing-lg)",
19
+ };
20
+
21
+ const emptyStyle: CSSProperties = {
22
+ textAlign: "center",
23
+ padding: "var(--spacing-2xl)",
24
+ color: "var(--color-text-muted)",
25
+ fontSize: "var(--font-size-lg)",
26
+ };
27
+
28
+ export const PostList = ({ posts }: PostListProps): JSX.Element => {
29
+ if (posts.length === 0) {
30
+ return <div style={emptyStyle}>{siteConfig.messages.noPosts}</div>;
31
+ }
32
+
33
+ return (
34
+ <div style={listStyle}>
35
+ {posts.map(
36
+ (post: PostSummary): JSX.Element => (
37
+ <PostCard key={post.slug} post={post} />
38
+ )
39
+ )}
40
+ </div>
41
+ );
42
+ };
src/client/components/common/Head.tsx ADDED
@@ -0,0 +1,46 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ //
2
+ // SPDX-FileCopyrightText: Hadad <hadad@linuxmail.org>
3
+ // SPDX-License-Identifier: Apache-2.0
4
+ //
5
+
6
+ import { Helmet } from "react-helmet-async";
7
+ import { siteConfig } from "@shared/config";
8
+
9
+ interface HeadProps {
10
+ title?: string;
11
+ description?: string;
12
+ image?: string;
13
+ url?: string;
14
+ type?: string;
15
+ }
16
+
17
+ export const Head = ({
18
+ title = siteConfig.title,
19
+ description = siteConfig.description,
20
+ image,
21
+ url,
22
+ type = "website",
23
+ }: HeadProps): JSX.Element => {
24
+ const fullTitle =
25
+ title === siteConfig.title ? title : `${title} - ${siteConfig.title}`;
26
+
27
+ return (
28
+ <Helmet>
29
+ <title>{fullTitle}</title>
30
+ <meta name="description" content={description} />
31
+
32
+ <meta property="og:type" content={type} />
33
+ <meta property="og:title" content={fullTitle} />
34
+ <meta property="og:description" content={description} />
35
+ {url && <meta property="og:url" content={url} />}
36
+ {image && <meta property="og:image" content={image} />}
37
+
38
+ <meta name="twitter:card" content="summary_large_image" />
39
+ <meta name="twitter:title" content={fullTitle} />
40
+ <meta name="twitter:description" content={description} />
41
+ {image && <meta name="twitter:image" content={image} />}
42
+
43
+ <link rel="canonical" href={url} />
44
+ </Helmet>
45
+ );
46
+ };
src/client/components/layout/Footer.tsx ADDED
@@ -0,0 +1,53 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ //
2
+ // SPDX-FileCopyrightText: Hadad <hadad@linuxmail.org>
3
+ // SPDX-License-Identifier: Apache-2.0
4
+ //
5
+
6
+ import { siteConfig } from "@shared/config";
7
+ import type { CSSProperties } from "react";
8
+
9
+ const footerStyle: CSSProperties = {
10
+ marginTop: "auto",
11
+ borderTop: "1px solid var(--color-border)",
12
+ padding: "var(--spacing-lg) 0",
13
+ backgroundColor: "var(--color-surface)",
14
+ };
15
+
16
+ const footerContainerStyle: CSSProperties = {
17
+ maxWidth: "var(--max-width-container)",
18
+ margin: "0 auto",
19
+ padding: "0 var(--spacing-md)",
20
+ textAlign: "center",
21
+ };
22
+
23
+ const footerTextStyle: CSSProperties = {
24
+ fontSize: "var(--font-size-sm)",
25
+ color: "var(--color-text-muted)",
26
+ margin: 0,
27
+ };
28
+
29
+ const footerLinkStyle: CSSProperties = {
30
+ color: "var(--color-accent)",
31
+ textDecoration: "none",
32
+ fontWeight: 500,
33
+ };
34
+
35
+ export const Footer = (): JSX.Element => {
36
+ return (
37
+ <footer style={footerStyle}>
38
+ <div style={footerContainerStyle}>
39
+ <p style={footerTextStyle}>
40
+ {siteConfig.footer.copyrightText} © {siteConfig.footer.copyrightYear}{" "}
41
+ <a
42
+ href={siteConfig.author.linkedin}
43
+ target="_blank"
44
+ rel="noopener noreferrer"
45
+ style={footerLinkStyle}
46
+ >
47
+ {siteConfig.author.name}
48
+ </a>
49
+ </p>
50
+ </div>
51
+ </footer>
52
+ );
53
+ };
src/client/components/layout/Header.tsx ADDED
@@ -0,0 +1,60 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ //
2
+ // SPDX-FileCopyrightText: Hadad <hadad@linuxmail.org>
3
+ // SPDX-License-Identifier: Apache-2.0
4
+ //
5
+
6
+ import { Link } from "react-router-dom";
7
+ import { siteConfig } from "@shared/config";
8
+ import type { CSSProperties } from "react";
9
+
10
+ const headerStyle: CSSProperties = {
11
+ position: "sticky",
12
+ top: 0,
13
+ zIndex: 100,
14
+ backgroundColor: "var(--color-background)",
15
+ borderBottom: "1px solid var(--color-border)",
16
+ padding: "var(--spacing-md) 0",
17
+ };
18
+
19
+ const headerContainerStyle: CSSProperties = {
20
+ maxWidth: "var(--max-width-container)",
21
+ margin: "0 auto",
22
+ padding: "0 var(--spacing-md)",
23
+ display: "flex",
24
+ alignItems: "center",
25
+ justifyContent: "center",
26
+ };
27
+
28
+ const logoLinkStyle: CSSProperties = {
29
+ display: "flex",
30
+ alignItems: "center",
31
+ gap: "var(--spacing-sm)",
32
+ color: "var(--color-text-primary)",
33
+ fontWeight: 600,
34
+ fontSize: "var(--font-size-xl)",
35
+ textDecoration: "none",
36
+ };
37
+
38
+ const profileImageStyle: CSSProperties = {
39
+ width: "36px",
40
+ height: "36px",
41
+ borderRadius: "50%",
42
+ objectFit: "cover",
43
+ };
44
+
45
+ export const Header = (): JSX.Element => {
46
+ return (
47
+ <header style={headerStyle}>
48
+ <div style={headerContainerStyle}>
49
+ <Link to="/" style={logoLinkStyle}>
50
+ <img
51
+ src="/assets/images/profile.png"
52
+ alt={siteConfig.name}
53
+ style={profileImageStyle}
54
+ />
55
+ <span>{siteConfig.description}</span>
56
+ </Link>
57
+ </div>
58
+ </header>
59
+ );
60
+ };
src/client/components/layout/Layout.tsx ADDED
@@ -0,0 +1,36 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ //
2
+ // SPDX-FileCopyrightText: Hadad <hadad@linuxmail.org>
3
+ // SPDX-License-Identifier: Apache-2.0
4
+ //
5
+
6
+ import { Header } from "./Header";
7
+ import { Footer } from "./Footer";
8
+ import type { ReactNode, CSSProperties } from "react";
9
+
10
+ interface LayoutProps {
11
+ children: ReactNode;
12
+ }
13
+
14
+ const layoutStyle: CSSProperties = {
15
+ minHeight: "100vh",
16
+ display: "flex",
17
+ flexDirection: "column",
18
+ };
19
+
20
+ const mainStyle: CSSProperties = {
21
+ flex: 1,
22
+ width: "100%",
23
+ maxWidth: "var(--max-width-container)",
24
+ margin: "0 auto",
25
+ padding: "var(--spacing-xl) var(--spacing-md)",
26
+ };
27
+
28
+ export const Layout = ({ children }: LayoutProps): JSX.Element => {
29
+ return (
30
+ <div style={layoutStyle}>
31
+ <Header />
32
+ <main style={mainStyle}>{children}</main>
33
+ <Footer />
34
+ </div>
35
+ );
36
+ };
src/client/hooks/usePosts.ts ADDED
@@ -0,0 +1,84 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ //
2
+ // SPDX-FileCopyrightText: Hadad <hadad@linuxmail.org>
3
+ // SPDX-License-Identifier: Apache-2.0
4
+ //
5
+
6
+ import { useState, useEffect, useCallback } from "react";
7
+ import type { Post, PostSummary, ApiResponse } from "@shared/types";
8
+
9
+ interface UsePostsResult {
10
+ posts: PostSummary[];
11
+ loading: boolean;
12
+ error: string | null;
13
+ refetch: () => Promise<void>;
14
+ }
15
+
16
+ interface UsePostResult {
17
+ post: Post | null;
18
+ loading: boolean;
19
+ error: string | null;
20
+ }
21
+
22
+ export const usePosts = (): UsePostsResult => {
23
+ const [posts, setPosts] = useState<PostSummary[]>([]);
24
+ const [loading, setLoading] = useState<boolean>(true);
25
+ const [error, setError] = useState<string | null>(null);
26
+
27
+ const fetchPosts = useCallback(async (): Promise<void> => {
28
+ setLoading(true);
29
+ setError(null);
30
+
31
+ try {
32
+ const response = await fetch("/api/posts");
33
+ const result: ApiResponse<PostSummary[]> = await response.json();
34
+
35
+ if (result.success && result.data) {
36
+ setPosts(result.data);
37
+ } else {
38
+ setError(result.error || "Failed to fetch posts");
39
+ }
40
+ } catch (fetchError) {
41
+ setError("Failed to connect to server");
42
+ } finally {
43
+ setLoading(false);
44
+ }
45
+ }, []);
46
+
47
+ useEffect((): void => {
48
+ fetchPosts();
49
+ }, [fetchPosts]);
50
+
51
+ return { posts, loading, error, refetch: fetchPosts };
52
+ };
53
+
54
+ export const usePost = (slug: string): UsePostResult => {
55
+ const [post, setPost] = useState<Post | null>(null);
56
+ const [loading, setLoading] = useState<boolean>(true);
57
+ const [error, setError] = useState<string | null>(null);
58
+
59
+ useEffect((): void => {
60
+ const fetchPost = async (): Promise<void> => {
61
+ setLoading(true);
62
+ setError(null);
63
+
64
+ try {
65
+ const response = await fetch(`/api/posts/${slug}`);
66
+ const result: ApiResponse<Post> = await response.json();
67
+
68
+ if (result.success && result.data) {
69
+ setPost(result.data);
70
+ } else {
71
+ setError(result.error || "Post not found");
72
+ }
73
+ } catch (fetchError) {
74
+ setError("Failed to connect to server");
75
+ } finally {
76
+ setLoading(false);
77
+ }
78
+ };
79
+
80
+ fetchPost();
81
+ }, [slug]);
82
+
83
+ return { post, loading, error };
84
+ };
src/client/main.tsx ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ //
2
+ // SPDX-FileCopyrightText: Hadad <hadad@linuxmail.org>
3
+ // SPDX-License-Identifier: Apache-2.0
4
+ //
5
+
6
+ import { StrictMode } from "react";
7
+ import { createRoot } from "react-dom/client";
8
+ import { HelmetProvider } from "react-helmet-async";
9
+ import { App } from "./App";
10
+ import "./styles/global.css";
11
+
12
+ const rootElement = document.getElementById("root");
13
+
14
+ if (rootElement) {
15
+ const root = createRoot(rootElement);
16
+
17
+ root.render(
18
+ <StrictMode>
19
+ <HelmetProvider>
20
+ <App />
21
+ </HelmetProvider>
22
+ </StrictMode>
23
+ );
24
+ }
src/client/pages/HomePage.tsx ADDED
@@ -0,0 +1,84 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ //
2
+ // SPDX-FileCopyrightText: Hadad <hadad@linuxmail.org>
3
+ // SPDX-License-Identifier: Apache-2.0
4
+ //
5
+
6
+ import { usePosts } from "../hooks/usePosts";
7
+ import { PostList } from "../components/blog/PostList";
8
+ import { Head } from "../components/common/Head";
9
+ import { siteConfig } from "@shared/config";
10
+ import { Loader, AlertCircle } from "lucide-react";
11
+ import type { CSSProperties } from "react";
12
+
13
+ const containerStyle: CSSProperties = {
14
+ maxWidth: "var(--max-width-content)",
15
+ margin: "0 auto",
16
+ };
17
+
18
+ const headingStyle: CSSProperties = {
19
+ fontSize: "var(--font-size-3xl)",
20
+ fontWeight: 700,
21
+ marginBottom: "var(--spacing-xl)",
22
+ color: "var(--color-text-primary)",
23
+ textAlign: "center",
24
+ };
25
+
26
+ const loadingContainerStyle: CSSProperties = {
27
+ display: "flex",
28
+ flexDirection: "column",
29
+ alignItems: "center",
30
+ justifyContent: "center",
31
+ padding: "var(--spacing-2xl)",
32
+ gap: "var(--spacing-md)",
33
+ color: "var(--color-text-muted)",
34
+ };
35
+
36
+ const errorContainerStyle: CSSProperties = {
37
+ display: "flex",
38
+ flexDirection: "column",
39
+ alignItems: "center",
40
+ justifyContent: "center",
41
+ padding: "var(--spacing-2xl)",
42
+ gap: "var(--spacing-md)",
43
+ color: "var(--color-text-muted)",
44
+ textAlign: "center",
45
+ };
46
+
47
+ const spinnerStyle: CSSProperties = {
48
+ animation: "spin 1s linear infinite",
49
+ };
50
+
51
+ export const HomePage = (): JSX.Element => {
52
+ const { posts, loading, error } = usePosts();
53
+
54
+ return (
55
+ <div style={containerStyle}>
56
+ <Head title={siteConfig.title} description={siteConfig.description} />
57
+
58
+ <h1 style={headingStyle}>{siteConfig.messages.latestArticles}</h1>
59
+
60
+ {loading && (
61
+ <div style={loadingContainerStyle}>
62
+ <Loader size={32} style={spinnerStyle} />
63
+ <span>{siteConfig.messages.loading}</span>
64
+ </div>
65
+ )}
66
+
67
+ {error && (
68
+ <div style={errorContainerStyle}>
69
+ <AlertCircle size={32} />
70
+ <span>{error}</span>
71
+ </div>
72
+ )}
73
+
74
+ {!loading && !error && <PostList posts={posts} />}
75
+
76
+ <style>{`
77
+ @keyframes spin {
78
+ from { transform: rotate(0deg); }
79
+ to { transform: rotate(360deg); }
80
+ }
81
+ `}</style>
82
+ </div>
83
+ );
84
+ };
src/client/pages/PostPage.tsx ADDED
@@ -0,0 +1,91 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ //
2
+ // SPDX-FileCopyrightText: Hadad <hadad@linuxmail.org>
3
+ // SPDX-License-Identifier: Apache-2.0
4
+ //
5
+
6
+ import { useParams, Link } from "react-router-dom";
7
+ import { usePost } from "../hooks/usePosts";
8
+ import { PostContent } from "../components/blog/PostContent";
9
+ import { Head } from "../components/common/Head";
10
+ import { siteConfig } from "@shared/config";
11
+ import { Loader, AlertCircle, ArrowLeft } from "lucide-react";
12
+ import type { CSSProperties } from "react";
13
+
14
+ const loadingContainerStyle: CSSProperties = {
15
+ display: "flex",
16
+ flexDirection: "column",
17
+ alignItems: "center",
18
+ justifyContent: "center",
19
+ padding: "var(--spacing-2xl)",
20
+ gap: "var(--spacing-md)",
21
+ color: "var(--color-text-muted)",
22
+ };
23
+
24
+ const errorContainerStyle: CSSProperties = {
25
+ display: "flex",
26
+ flexDirection: "column",
27
+ alignItems: "center",
28
+ justifyContent: "center",
29
+ padding: "var(--spacing-2xl)",
30
+ gap: "var(--spacing-md)",
31
+ color: "var(--color-text-muted)",
32
+ textAlign: "center",
33
+ };
34
+
35
+ const backLinkStyle: CSSProperties = {
36
+ display: "inline-flex",
37
+ alignItems: "center",
38
+ gap: "var(--spacing-xs)",
39
+ color: "var(--color-accent)",
40
+ marginTop: "var(--spacing-md)",
41
+ textDecoration: "none",
42
+ };
43
+
44
+ const spinnerStyle: CSSProperties = {
45
+ animation: "spin 1s linear infinite",
46
+ };
47
+
48
+ export const PostPage = (): JSX.Element => {
49
+ const { slug } = useParams<{ slug: string }>();
50
+ const { post, loading, error } = usePost(slug || "");
51
+
52
+ if (loading) {
53
+ return (
54
+ <div style={loadingContainerStyle}>
55
+ <Loader size={32} style={spinnerStyle} />
56
+ <span>{siteConfig.messages.loading}</span>
57
+ <style>{`
58
+ @keyframes spin {
59
+ from { transform: rotate(0deg); }
60
+ to { transform: rotate(360deg); }
61
+ }
62
+ `}</style>
63
+ </div>
64
+ );
65
+ }
66
+
67
+ if (error || !post) {
68
+ return (
69
+ <div style={errorContainerStyle}>
70
+ <AlertCircle size={32} />
71
+ <span>{error || siteConfig.messages.postNotFound}</span>
72
+ <Link to="/" style={backLinkStyle}>
73
+ <ArrowLeft size={16} />
74
+ {siteConfig.messages.backToHome}
75
+ </Link>
76
+ </div>
77
+ );
78
+ }
79
+
80
+ return (
81
+ <>
82
+ <Head
83
+ title={post.frontMatter.title}
84
+ description={post.frontMatter.description}
85
+ image={post.frontMatter.image}
86
+ type="article"
87
+ />
88
+ <PostContent post={post} />
89
+ </>
90
+ );
91
+ };
src/client/styles/global.css ADDED
@@ -0,0 +1,387 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ /*
2
+ * SPDX-FileCopyrightText: Hadad <hadad@linuxmail.org>
3
+ * SPDX-License-Identifier: Apache-2.0
4
+ */
5
+
6
+ *,
7
+ *::before,
8
+ *::after {
9
+ box-sizing: border-box;
10
+ margin: 0;
11
+ padding: 0;
12
+ }
13
+
14
+ :root {
15
+ --color-background: #ffffff;
16
+ --color-surface: #f8f9fa;
17
+ --color-text-primary: #1a1a2e;
18
+ --color-text-secondary: #4a4a68;
19
+ --color-text-muted: #6c6c80;
20
+ --color-accent: #3b82f6;
21
+ --color-accent-hover: #2563eb;
22
+ --color-border: #e5e7eb;
23
+ --color-code-background: #1e1e2e;
24
+ --color-code-text: #cdd6f4;
25
+ --font-family-base: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto,
26
+ "Helvetica Neue", Arial, sans-serif;
27
+ --font-family-mono: "SF Mono", Monaco, "Cascadia Code", "Roboto Mono",
28
+ Consolas, monospace;
29
+ --font-size-xs: clamp(0.625rem, 1.5vw, 0.75rem);
30
+ --font-size-sm: clamp(0.75rem, 1.8vw, 0.875rem);
31
+ --font-size-base: clamp(0.875rem, 2vw, 1rem);
32
+ --font-size-lg: clamp(1rem, 2.2vw, 1.125rem);
33
+ --font-size-xl: clamp(1.125rem, 2.5vw, 1.25rem);
34
+ --font-size-2xl: clamp(1.25rem, 3vw, 1.5rem);
35
+ --font-size-3xl: clamp(1.5rem, 3.5vw, 1.875rem);
36
+ --font-size-4xl: clamp(1.75rem, 4vw, 2.25rem);
37
+ --spacing-xs: clamp(0.25rem, 1vw, 0.5rem);
38
+ --spacing-sm: clamp(0.5rem, 1.5vw, 0.75rem);
39
+ --spacing-md: clamp(0.75rem, 2vw, 1rem);
40
+ --spacing-lg: clamp(1rem, 2.5vw, 1.5rem);
41
+ --spacing-xl: clamp(1.5rem, 3vw, 2rem);
42
+ --spacing-2xl: clamp(2rem, 4vw, 3rem);
43
+ --max-width-content: min(90vw, 720px);
44
+ --max-width-container: min(95vw, 1024px);
45
+ --border-radius-sm: 4px;
46
+ --border-radius-md: 8px;
47
+ --border-radius-lg: 12px;
48
+ --transition-fast: 150ms ease;
49
+ --transition-base: 250ms ease;
50
+ --shadow-sm: 0 1px 2px rgba(0, 0, 0, 0.05);
51
+ --shadow-md: 0 4px 6px -1px rgba(0, 0, 0, 0.1);
52
+ --shadow-lg: 0 10px 15px -3px rgba(0, 0, 0, 0.1);
53
+ --line-height-tight: 1.4;
54
+ --line-height-base: 1.75;
55
+ --line-height-relaxed: 2;
56
+ }
57
+
58
+ html {
59
+ font-size: 16px;
60
+ scroll-behavior: smooth;
61
+ -webkit-text-size-adjust: 100%;
62
+ text-size-adjust: 100%;
63
+ }
64
+
65
+ body {
66
+ font-family: var(--font-family-base);
67
+ font-size: var(--font-size-base);
68
+ line-height: var(--line-height-base);
69
+ color: var(--color-text-primary);
70
+ background-color: var(--color-background);
71
+ min-height: 100vh;
72
+ overflow-x: hidden;
73
+ -webkit-font-smoothing: antialiased;
74
+ -moz-osx-font-smoothing: grayscale;
75
+ }
76
+
77
+ #root {
78
+ min-height: 100vh;
79
+ display: flex;
80
+ flex-direction: column;
81
+ }
82
+
83
+ a {
84
+ color: var(--color-accent);
85
+ text-decoration: none;
86
+ transition: color var(--transition-fast);
87
+ }
88
+
89
+ a:hover {
90
+ color: var(--color-accent-hover);
91
+ }
92
+
93
+ img,
94
+ video,
95
+ audio {
96
+ max-width: 100%;
97
+ height: auto;
98
+ display: block;
99
+ }
100
+
101
+ h1,
102
+ h2,
103
+ h3,
104
+ h4,
105
+ h5,
106
+ h6 {
107
+ line-height: var(--line-height-tight);
108
+ font-weight: 600;
109
+ color: var(--color-text-primary);
110
+ margin-top: var(--spacing-xl);
111
+ margin-bottom: var(--spacing-md);
112
+ }
113
+
114
+ h1:first-child,
115
+ h2:first-child,
116
+ h3:first-child,
117
+ h4:first-child,
118
+ h5:first-child,
119
+ h6:first-child {
120
+ margin-top: 0;
121
+ }
122
+
123
+ h1 {
124
+ font-size: var(--font-size-4xl);
125
+ }
126
+
127
+ h2 {
128
+ font-size: var(--font-size-3xl);
129
+ }
130
+
131
+ h3 {
132
+ font-size: var(--font-size-2xl);
133
+ }
134
+
135
+ h4 {
136
+ font-size: var(--font-size-xl);
137
+ }
138
+
139
+ h5 {
140
+ font-size: var(--font-size-lg);
141
+ }
142
+
143
+ h6 {
144
+ font-size: var(--font-size-base);
145
+ }
146
+
147
+ p {
148
+ margin-bottom: var(--spacing-lg);
149
+ line-height: var(--line-height-relaxed);
150
+ }
151
+
152
+ ul,
153
+ ol {
154
+ margin-left: var(--spacing-lg);
155
+ margin-bottom: var(--spacing-lg);
156
+ padding-left: var(--spacing-lg);
157
+ line-height: var(--line-height-relaxed);
158
+ }
159
+
160
+ ul {
161
+ list-style-type: disc;
162
+ }
163
+
164
+ ol {
165
+ list-style-type: decimal;
166
+ }
167
+
168
+ ul ul,
169
+ ol ol,
170
+ ul ol,
171
+ ol ul {
172
+ margin-top: var(--spacing-sm);
173
+ margin-bottom: var(--spacing-sm);
174
+ }
175
+
176
+ li {
177
+ margin-bottom: var(--spacing-sm);
178
+ padding-left: var(--spacing-xs);
179
+ }
180
+
181
+ li::marker {
182
+ color: var(--color-accent);
183
+ }
184
+
185
+ li > p {
186
+ margin-bottom: var(--spacing-sm);
187
+ }
188
+
189
+ li > ul,
190
+ li > ol {
191
+ margin-top: var(--spacing-sm);
192
+ }
193
+
194
+ blockquote {
195
+ border-left: 4px solid var(--color-accent);
196
+ padding-left: var(--spacing-lg);
197
+ padding-top: var(--spacing-sm);
198
+ padding-bottom: var(--spacing-sm);
199
+ margin: var(--spacing-lg) 0;
200
+ font-style: italic;
201
+ color: var(--color-text-secondary);
202
+ background-color: var(--color-surface);
203
+ border-radius: 0 var(--border-radius-md) var(--border-radius-md) 0;
204
+ line-height: var(--line-height-relaxed);
205
+ }
206
+
207
+ blockquote p {
208
+ margin-bottom: var(--spacing-sm);
209
+ }
210
+
211
+ blockquote p:last-child {
212
+ margin-bottom: 0;
213
+ }
214
+
215
+ code {
216
+ font-family: var(--font-family-mono);
217
+ font-size: 0.9em;
218
+ background-color: var(--color-code-background);
219
+ color: var(--color-code-text);
220
+ padding: 0.2em 0.4em;
221
+ border-radius: var(--border-radius-sm);
222
+ }
223
+
224
+ pre {
225
+ background-color: var(--color-code-background);
226
+ padding: var(--spacing-lg);
227
+ border-radius: var(--border-radius-md);
228
+ overflow-x: auto;
229
+ margin: var(--spacing-lg) 0;
230
+ }
231
+
232
+ pre code {
233
+ background: none;
234
+ padding: 0;
235
+ font-size: var(--font-size-sm);
236
+ line-height: var(--line-height-base);
237
+ }
238
+
239
+ .hljs {
240
+ background: var(--color-code-background);
241
+ color: var(--color-code-text);
242
+ }
243
+
244
+ .hljs-keyword,
245
+ .hljs-selector-tag,
246
+ .hljs-built_in,
247
+ .hljs-name,
248
+ .hljs-tag {
249
+ color: #cba6f7;
250
+ }
251
+
252
+ .hljs-string,
253
+ .hljs-title,
254
+ .hljs-section,
255
+ .hljs-attribute,
256
+ .hljs-literal,
257
+ .hljs-template-tag,
258
+ .hljs-template-variable,
259
+ .hljs-type,
260
+ .hljs-addition {
261
+ color: #a6e3a1;
262
+ }
263
+
264
+ .hljs-comment,
265
+ .hljs-quote,
266
+ .hljs-deletion,
267
+ .hljs-meta {
268
+ color: #6c7086;
269
+ }
270
+
271
+ .hljs-keyword,
272
+ .hljs-selector-tag,
273
+ .hljs-literal,
274
+ .hljs-doctag,
275
+ .hljs-title,
276
+ .hljs-section,
277
+ .hljs-type,
278
+ .hljs-selector-id {
279
+ font-weight: 600;
280
+ }
281
+
282
+ .hljs-symbol,
283
+ .hljs-bullet,
284
+ .hljs-link {
285
+ color: #f9e2af;
286
+ }
287
+
288
+ .hljs-number,
289
+ .hljs-regexp {
290
+ color: #fab387;
291
+ }
292
+
293
+ .hljs-variable,
294
+ .hljs-template-variable,
295
+ .hljs-attr {
296
+ color: #89dceb;
297
+ }
298
+
299
+ .hljs-function {
300
+ color: #89b4fa;
301
+ }
302
+
303
+ .hljs-params {
304
+ color: #f38ba8;
305
+ }
306
+
307
+ table {
308
+ width: 100%;
309
+ border-collapse: collapse;
310
+ margin: var(--spacing-lg) 0;
311
+ }
312
+
313
+ th,
314
+ td {
315
+ padding: var(--spacing-sm) var(--spacing-md);
316
+ border: 1px solid var(--color-border);
317
+ text-align: left;
318
+ line-height: var(--line-height-base);
319
+ }
320
+
321
+ th {
322
+ background-color: var(--color-surface);
323
+ font-weight: 600;
324
+ }
325
+
326
+ hr {
327
+ border: none;
328
+ border-top: 1px solid var(--color-border);
329
+ margin: var(--spacing-2xl) 0;
330
+ }
331
+
332
+ iframe {
333
+ max-width: 100%;
334
+ border: none;
335
+ border-radius: var(--border-radius-md);
336
+ }
337
+
338
+ ::selection {
339
+ background-color: var(--color-accent);
340
+ color: var(--color-background);
341
+ }
342
+
343
+ @media (prefers-color-scheme: dark) {
344
+ :root {
345
+ --color-background: oklch(0.263 0 0);
346
+ --color-surface: oklch(0.32 0 0);
347
+ --color-text-primary: #f5f5f7;
348
+ --color-text-secondary: #c5c5d0;
349
+ --color-text-muted: #9898a8;
350
+ --color-accent: #60a5fa;
351
+ --color-accent-hover: #93c5fd;
352
+ --color-border: oklch(0.4 0 0);
353
+ --color-code-background: oklch(0.22 0 0);
354
+ --color-code-text: #e2e8f0;
355
+ }
356
+
357
+ .hljs-comment,
358
+ .hljs-quote,
359
+ .hljs-deletion,
360
+ .hljs-meta {
361
+ color: #8888a0;
362
+ }
363
+ }
364
+
365
+ @media (max-width: 320px) {
366
+ html {
367
+ font-size: 14px;
368
+ }
369
+ }
370
+
371
+ @media (min-width: 1920px) {
372
+ html {
373
+ font-size: 18px;
374
+ }
375
+ }
376
+
377
+ @media (min-width: 2560px) {
378
+ html {
379
+ font-size: 20px;
380
+ }
381
+ }
382
+
383
+ @media (min-width: 3840px) {
384
+ html {
385
+ font-size: 24px;
386
+ }
387
+ }
src/server/index.ts ADDED
@@ -0,0 +1,64 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ //
2
+ // SPDX-FileCopyrightText: Hadad <hadad@linuxmail.org>
3
+ // SPDX-License-Identifier: Apache-2.0
4
+ //
5
+
6
+ import express, { Application, Request, Response, NextFunction } from "express";
7
+ import cors from "cors";
8
+ import { fileURLToPath } from "url";
9
+ import { dirname, join } from "path";
10
+ import { apiRoutes } from "./routes/apiRoutes.js";
11
+ import { initializeFileWatcher } from "./utils/fileWatcher.js";
12
+ import { initializePostService } from "./services/postService.js";
13
+
14
+ const __filename = fileURLToPath(import.meta.url);
15
+ const __dirname = dirname(__filename);
16
+
17
+ const HOST: string = "0.0.0.0";
18
+ const PORT: number = 3000;
19
+
20
+ const app: Application = express();
21
+
22
+ app.use(cors({
23
+ origin: true,
24
+ methods: ["GET"],
25
+ allowedHeaders: ["Content-Type"],
26
+ }));
27
+
28
+ app.use(express.json({ limit: "1mb" }));
29
+
30
+ app.use("/api", apiRoutes);
31
+
32
+ const clientDistPath: string = join(__dirname, "../client");
33
+ app.use(express.static(clientDistPath));
34
+
35
+ app.get("*", (_request: Request, response: Response): void => {
36
+ const indexPath: string = join(clientDistPath, "index.html");
37
+ response.sendFile(indexPath);
38
+ });
39
+
40
+ app.use(
41
+ (
42
+ error: Error,
43
+ _request: Request,
44
+ response: Response,
45
+ _next: NextFunction
46
+ ): void => {
47
+ console.error("Server Error:", error.message);
48
+ response.status(500).json({
49
+ success: false,
50
+ error: "Internal Server Error",
51
+ });
52
+ }
53
+ );
54
+
55
+ const startServer = async (): Promise<void> => {
56
+ await initializePostService();
57
+ initializeFileWatcher();
58
+
59
+ app.listen(PORT, HOST, (): void => {
60
+ console.log(`Server running at http://${HOST}:${PORT}`);
61
+ });
62
+ };
63
+
64
+ startServer();
src/server/routes/apiRoutes.ts ADDED
@@ -0,0 +1,85 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ //
2
+ // SPDX-FileCopyrightText: Hadad <hadad@linuxmail.org>
3
+ // SPDX-License-Identifier: Apache-2.0
4
+ //
5
+
6
+ import { Router, Request, Response } from "express";
7
+ import { getAllPosts, getPostBySlug } from "../services/postService.js";
8
+ import type { ApiResponse, Post, PostSummary } from "../../shared/types.js";
9
+
10
+ export const apiRoutes: Router = Router();
11
+
12
+ apiRoutes.get(
13
+ "/posts",
14
+ async (_request: Request, response: Response): Promise<void> => {
15
+ try {
16
+ const posts: PostSummary[] = await getAllPosts();
17
+ const apiResponse: ApiResponse<PostSummary[]> = {
18
+ success: true,
19
+ data: posts,
20
+ };
21
+ response.json(apiResponse);
22
+ } catch (error) {
23
+ const errorMessage =
24
+ error instanceof Error ? error.message : "Unknown error";
25
+ const apiResponse: ApiResponse<null> = {
26
+ success: false,
27
+ error: errorMessage,
28
+ };
29
+ response.status(500).json(apiResponse);
30
+ }
31
+ }
32
+ );
33
+
34
+ apiRoutes.get(
35
+ "/posts/:slug",
36
+ async (request: Request, response: Response): Promise<void> => {
37
+ try {
38
+ const slug: string = request.params.slug;
39
+ const post: Post | null = await getPostBySlug(slug);
40
+
41
+ if (!post) {
42
+ const apiResponse: ApiResponse<null> = {
43
+ success: false,
44
+ error: "Post not found",
45
+ };
46
+ response.status(404).json(apiResponse);
47
+ return;
48
+ }
49
+
50
+ const apiResponse: ApiResponse<Post> = {
51
+ success: true,
52
+ data: post,
53
+ };
54
+ response.json(apiResponse);
55
+ } catch (error) {
56
+ const errorMessage =
57
+ error instanceof Error ? error.message : "Unknown error";
58
+ const apiResponse: ApiResponse<null> = {
59
+ success: false,
60
+ error: errorMessage,
61
+ };
62
+ response.status(500).json(apiResponse);
63
+ }
64
+ }
65
+ );
66
+
67
+ apiRoutes.all(
68
+ "/posts",
69
+ (_request: Request, response: Response): void => {
70
+ response.status(405).json({
71
+ success: false,
72
+ error: "Method not allowed",
73
+ });
74
+ }
75
+ );
76
+
77
+ apiRoutes.all(
78
+ "/posts/:slug",
79
+ (_request: Request, response: Response): void => {
80
+ response.status(405).json({
81
+ success: false,
82
+ error: "Method not allowed",
83
+ });
84
+ }
85
+ );
src/server/services/postService.ts ADDED
@@ -0,0 +1,94 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ //
2
+ // SPDX-FileCopyrightText: Hadad <hadad@linuxmail.org>
3
+ // SPDX-License-Identifier: Apache-2.0
4
+ //
5
+
6
+ import { readdir, readFile, stat } from "fs/promises";
7
+ import { join } from "path";
8
+ import { fileURLToPath } from "url";
9
+ import { dirname } from "path";
10
+ import { parseMarkdown, extractFrontMatter } from "../utils/markdownParser.js";
11
+ import type { Post, PostSummary, PostFrontMatter } from "../../shared/types.js";
12
+
13
+ const __filename = fileURLToPath(import.meta.url);
14
+ const __dirname = dirname(__filename);
15
+
16
+ const POSTS_DIRECTORY: string = join(__dirname, "../../../post");
17
+
18
+ const postsCache: Map<string, Post> = new Map();
19
+
20
+ export const initializePostService = async (): Promise<void> => {
21
+ await loadAllPosts();
22
+ };
23
+
24
+ export const loadAllPosts = async (): Promise<void> => {
25
+ try {
26
+ const files: string[] = await readdir(POSTS_DIRECTORY);
27
+ const markdownFiles: string[] = files.filter(
28
+ (file: string): boolean =>
29
+ file.endsWith(".md") || file.endsWith(".markdown")
30
+ );
31
+
32
+ postsCache.clear();
33
+
34
+ for (const file of markdownFiles) {
35
+ await loadPost(file);
36
+ }
37
+
38
+ console.log(`Loaded ${postsCache.size} posts`);
39
+ } catch (error) {
40
+ console.error("Error loading posts:", error);
41
+ }
42
+ };
43
+
44
+ export const loadPost = async (filename: string): Promise<void> => {
45
+ try {
46
+ const filePath: string = join(POSTS_DIRECTORY, filename);
47
+ const fileContent: string = await readFile(filePath, "utf-8");
48
+ const fileStat = await stat(filePath);
49
+
50
+ const slug: string = filename.replace(/\.(md|markdown)$/, "");
51
+ const frontMatter: PostFrontMatter = extractFrontMatter(fileContent);
52
+ const content: string = parseMarkdown(fileContent);
53
+
54
+ const post: Post = {
55
+ slug,
56
+ frontMatter,
57
+ content,
58
+ rawContent: fileContent,
59
+ lastModified: fileStat.mtimeMs,
60
+ };
61
+
62
+ postsCache.set(slug, post);
63
+ } catch (error) {
64
+ console.error(`Error loading post ${filename}:`, error);
65
+ }
66
+ };
67
+
68
+ export const removePost = (filename: string): void => {
69
+ const slug: string = filename.replace(/\.(md|markdown)$/, "");
70
+ postsCache.delete(slug);
71
+ console.log(`Removed post: ${slug}`);
72
+ };
73
+
74
+ export const getAllPosts = async (): Promise<PostSummary[]> => {
75
+ const posts: PostSummary[] = Array.from(postsCache.values())
76
+ .map(
77
+ (post: Post): PostSummary => ({
78
+ slug: post.slug,
79
+ frontMatter: post.frontMatter,
80
+ lastModified: post.lastModified,
81
+ })
82
+ )
83
+ .sort(
84
+ (a: PostSummary, b: PostSummary): number =>
85
+ new Date(b.frontMatter.date).getTime() -
86
+ new Date(a.frontMatter.date).getTime()
87
+ );
88
+
89
+ return posts;
90
+ };
91
+
92
+ export const getPostBySlug = async (slug: string): Promise<Post | null> => {
93
+ return postsCache.get(slug) || null;
94
+ };
src/server/utils/fileWatcher.ts ADDED
@@ -0,0 +1,69 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ //
2
+ // SPDX-FileCopyrightText: Hadad <hadad@linuxmail.org>
3
+ // SPDX-License-Identifier: Apache-2.0
4
+ //
5
+
6
+ import chokidar, { FSWatcher } from "chokidar";
7
+ import { join, basename } from "path";
8
+ import { fileURLToPath } from "url";
9
+ import { dirname } from "path";
10
+ import { loadPost, removePost } from "../services/postService.js";
11
+
12
+ const __filename = fileURLToPath(import.meta.url);
13
+ const __dirname = dirname(__filename);
14
+
15
+ const POSTS_DIRECTORY: string = join(__dirname, "../../../post");
16
+
17
+ let watcher: FSWatcher | null = null;
18
+
19
+ const isMarkdownFile = (filePath: string): boolean => {
20
+ return filePath.endsWith(".md") || filePath.endsWith(".markdown");
21
+ };
22
+
23
+ export const initializeFileWatcher = (): void => {
24
+ if (watcher) {
25
+ return;
26
+ }
27
+
28
+ watcher = chokidar.watch(POSTS_DIRECTORY, {
29
+ persistent: true,
30
+ ignoreInitial: true,
31
+ awaitWriteFinish: {
32
+ stabilityThreshold: 500,
33
+ pollInterval: 100,
34
+ },
35
+ });
36
+
37
+ watcher.on("add", (filePath: string): void => {
38
+ if (isMarkdownFile(filePath)) {
39
+ const filename: string = basename(filePath);
40
+ console.log(`New post detected: ${filename}`);
41
+ loadPost(filename);
42
+ }
43
+ });
44
+
45
+ watcher.on("change", (filePath: string): void => {
46
+ if (isMarkdownFile(filePath)) {
47
+ const filename: string = basename(filePath);
48
+ console.log(`Post updated: ${filename}`);
49
+ loadPost(filename);
50
+ }
51
+ });
52
+
53
+ watcher.on("unlink", (filePath: string): void => {
54
+ if (isMarkdownFile(filePath)) {
55
+ const filename: string = basename(filePath);
56
+ console.log(`Post deleted: ${filename}`);
57
+ removePost(filename);
58
+ }
59
+ });
60
+
61
+ console.log(`Watching for post changes in: ${POSTS_DIRECTORY}`);
62
+ };
63
+
64
+ export const stopFileWatcher = async (): Promise<void> => {
65
+ if (watcher) {
66
+ await watcher.close();
67
+ watcher = null;
68
+ }
69
+ };
src/server/utils/markdownParser.ts ADDED
@@ -0,0 +1,49 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ //
2
+ // SPDX-FileCopyrightText: Hadad <hadad@linuxmail.org>
3
+ // SPDX-License-Identifier: Apache-2.0
4
+ //
5
+
6
+ import { Marked } from "marked";
7
+ import { markedHighlight } from "marked-highlight";
8
+ import hljs from "highlight.js";
9
+ import frontMatter from "front-matter";
10
+ import type { PostFrontMatter } from "../../shared/types.js";
11
+ import { siteConfig } from "../../shared/config.js";
12
+
13
+ const marked = new Marked(
14
+ markedHighlight({
15
+ langPrefix: "hljs language-",
16
+ highlight(code: string, lang: string): string {
17
+ const language = hljs.getLanguage(lang) ? lang : "plaintext";
18
+ return hljs.highlight(code, { language }).value;
19
+ },
20
+ })
21
+ );
22
+
23
+ marked.setOptions({
24
+ gfm: true,
25
+ breaks: true,
26
+ });
27
+
28
+ export const parseMarkdown = (content: string): string => {
29
+ const parsed = frontMatter<PostFrontMatter>(content);
30
+ const htmlContent: string = marked.parse(parsed.body) as string;
31
+ return htmlContent;
32
+ };
33
+
34
+ export const extractFrontMatter = (content: string): PostFrontMatter => {
35
+ const parsed = frontMatter<PostFrontMatter>(content);
36
+
37
+ const defaultFrontMatter: PostFrontMatter = {
38
+ title: siteConfig.defaults.postTitle,
39
+ date: new Date().toISOString().split("T")[0],
40
+ description: siteConfig.defaults.postDescription,
41
+ author: siteConfig.defaults.postAuthor,
42
+ tags: [],
43
+ };
44
+
45
+ return {
46
+ ...defaultFrontMatter,
47
+ ...parsed.attributes,
48
+ };
49
+ };
src/shared/config.ts ADDED
@@ -0,0 +1,37 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ //
2
+ // SPDX-FileCopyrightText: Hadad <hadad@linuxmail.org>
3
+ // SPDX-License-Identifier: Apache-2.0
4
+ //
5
+
6
+ export const siteConfig = {
7
+ name: "Hadad Darajat",
8
+ title: "Hadad Darajat",
9
+ description: "Personal Blog",
10
+ locale: "en-US",
11
+ author: {
12
+ name: "Hadad Darajat",
13
+ linkedin: "https://linkedin.com/in/hadadrjt",
14
+ },
15
+ footer: {
16
+ copyrightYear: "2025",
17
+ copyrightText: "Copyright",
18
+ },
19
+ messages: {
20
+ loading: "Loading article...",
21
+ noPosts: "There are no post available at this time",
22
+ postNotFound: "Article not found",
23
+ backToHome: "Back to Home",
24
+ readMore: "Read more",
25
+ latestArticles: "Latest Articles",
26
+ },
27
+ defaults: {
28
+ postTitle: "Untitled",
29
+ postAuthor: "Anonymous",
30
+ postDescription: "",
31
+ },
32
+ dateFormat: {
33
+ year: "numeric" as const,
34
+ month: "long" as const,
35
+ day: "numeric" as const,
36
+ },
37
+ };
src/shared/types.ts ADDED
@@ -0,0 +1,33 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ //
2
+ // SPDX-FileCopyrightText: Hadad <hadad@linuxmail.org>
3
+ // SPDX-License-Identifier: Apache-2.0
4
+ //
5
+
6
+ export interface PostFrontMatter {
7
+ title: string;
8
+ date: string;
9
+ description: string;
10
+ author?: string;
11
+ tags?: string[];
12
+ image?: string;
13
+ }
14
+
15
+ export interface Post {
16
+ slug: string;
17
+ frontMatter: PostFrontMatter;
18
+ content: string;
19
+ rawContent: string;
20
+ lastModified: number;
21
+ }
22
+
23
+ export interface PostSummary {
24
+ slug: string;
25
+ frontMatter: PostFrontMatter;
26
+ lastModified: number;
27
+ }
28
+
29
+ export interface ApiResponse<T> {
30
+ success: boolean;
31
+ data?: T;
32
+ error?: string;
33
+ }
tsconfig.json ADDED
@@ -0,0 +1,37 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "compilerOptions": {
3
+ "target": "ES2022",
4
+ "useDefineForClassFields": true,
5
+ "lib": [
6
+ "ES2022",
7
+ "DOM",
8
+ "DOM.Iterable"
9
+ ],
10
+ "module": "ESNext",
11
+ "skipLibCheck": true,
12
+ "moduleResolution": "bundler",
13
+ "allowImportingTsExtensions": true,
14
+ "resolveJsonModule": true,
15
+ "isolatedModules": true,
16
+ "noEmit": true,
17
+ "jsx": "react-jsx",
18
+ "strict": true,
19
+ "noUnusedLocals": true,
20
+ "noUnusedParameters": true,
21
+ "noFallthroughCasesInSwitch": true,
22
+ "esModuleInterop": true,
23
+ "allowSyntheticDefaultImports": true,
24
+ "forceConsistentCasingInFileNames": true,
25
+ "baseUrl": ".",
26
+ "paths": {
27
+ "@shared/*": ["src/shared/*"],
28
+ "@client/*": ["src/client/*"],
29
+ "@server/*": ["src/server/*"]
30
+ }
31
+ },
32
+ "include": [
33
+ "src/client",
34
+ "src/shared"
35
+ ],
36
+ "references": [{ "path": "./tsconfig.node.json" }]
37
+ }
tsconfig.node.json ADDED
@@ -0,0 +1,12 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "compilerOptions": {
3
+ "composite": true,
4
+ "skipLibCheck": true,
5
+ "module": "ESNext",
6
+ "moduleResolution": "bundler",
7
+ "allowSyntheticDefaultImports": true,
8
+ "strict": true,
9
+ "noEmit": true
10
+ },
11
+ "include": ["vite.config.ts"]
12
+ }
tsconfig.server.json ADDED
@@ -0,0 +1,28 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "compilerOptions": {
3
+ "target": "ES2022",
4
+ "module": "ESNext",
5
+ "moduleResolution": "node",
6
+ "esModuleInterop": true,
7
+ "allowSyntheticDefaultImports": true,
8
+ "strict": true,
9
+ "skipLibCheck": true,
10
+ "forceConsistentCasingInFileNames": true,
11
+ "outDir": "dist",
12
+ "rootDir": "src",
13
+ "resolveJsonModule": true,
14
+ "declaration": false,
15
+ "sourceMap": true,
16
+ "noUnusedLocals": true,
17
+ "noUnusedParameters": true
18
+ },
19
+ "include": [
20
+ "src/server/**/*",
21
+ "src/shared/**/*"
22
+ ],
23
+ "exclude": [
24
+ "node_modules",
25
+ "dist",
26
+ "src/client"
27
+ ]
28
+ }
vite.config.ts ADDED
@@ -0,0 +1,35 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ //
2
+ // SPDX-FileCopyrightText: Hadad <hadad@linuxmail.org>
3
+ // SPDX-License-Identifier: Apache-2.0
4
+ //
5
+
6
+ import { defineConfig } from "vite";
7
+ import react from "@vitejs/plugin-react";
8
+ import { resolve } from "path";
9
+
10
+ export default defineConfig({
11
+ plugins: [react()],
12
+ root: ".",
13
+ publicDir: "public",
14
+
15
+ resolve: {
16
+ alias: {
17
+ "@client": resolve(__dirname, "src/client"),
18
+ "@shared": resolve(__dirname, "src/shared"),
19
+ },
20
+ },
21
+
22
+ build: {
23
+ outDir: "dist/client",
24
+ emptyOutDir: true,
25
+ },
26
+
27
+ server: {
28
+ proxy: {
29
+ "/api": {
30
+ target: "http://localhost:3000",
31
+ changeOrigin: true,
32
+ },
33
+ },
34
+ },
35
+ });