Well, I understand you won’t lose any sleep, but this is conceptually stupid.
That would be like refusing to allow someone to buy a house because the last owner was a convicted of a crime. Sorry, we gotta demolish the house now! And nobody can live on the plot.
The owner of this repo is free to do whatever they want but I’m free to point out that it’s a dumb practice.
> That would be like refusing to allow someone to ...
You should stop thinking by analogies. You're doing a disservice to yourself and your thinking capacity.
> The owner of this repo is free to do whatever they want but I’m free to point out that it’s a dumb practice.
I find it very useful, just like most of its users, and if ever I were to find it necessary to use a website that's obviously blocked, I know how to unblock it. Most of the time I don't bother, so that's something for you to think.
Personally I find that I prefer badly written english or auto-translated stuff written in languages foreign to me over ai generated or even just ai polished works I've seen. There is just so much more character, depth and variance there vs ultra ai generic or slop text.
That being said this project seems focused on content farms not people who just need a little help writing so this whole conversation is a bit of a side tangent.
One of my coworkers is EXTREMELY capable but functionally almost illiterate. He’s recently discovered that he can put an idea in Copilot and have it generate an email. So now instead of brief, correct, but difficult to parse emails we receive 20-paragraph, bulleted, formatted OpenAI slop. It’s been a very strange thing to see, like someone getting extraordinarily bad cosmetic surgery.
Capable doesn't mean capable of office work though, I could see someone with a language disorder doing electronics and have trouble with words, not numbers. Or someone who has trouble with written words specifically doing most of their learning with classes and videos.
Exactly right. The individual in question produces excellent deliverables within their space. They, the coworker, are very good at receiving inputs, but not very good at outputs (other than their deliverables). In a way, it's like having an offshore worker who speaks almost none of your language but can understand it and produce good work.
> like someone getting extraordinarily bad cosmetic surgery.
this is such an incredible way to phrase what it all looks like to the rest of us. and i suspect the people doing it, just like those with obvious cosmetic surgery, have no idea how weird and off it looks.
I have a similar coworker, but he's not great at prompting, so 10% of the time the AI version of himself makes confident assertions that he did not intend and are clearly not true. Genuinely no idea what I'm supposed to do about it.
Exactly right. He’s good at what he does, except communicating, and people are beginning to associate him with AI slop they don’t have time to read rather than the excellent work he does for them.
Yeah I hate it when people do that and I always call them out on it.
Unfortunately our company is trying to be "AI First" so they'll just point to that and continue their bullshit.
Our company literally promotes AI slop over personally made content even if it's mediocre crap. All they care about is rising usage numbers of things like copilot in office.
I mean, I know it is probably tongue in cheek but that never-asked-question was particularly out of place. Massively generated AI contents are usually not THAT thoughtful anyway.
From experience: If you don't know Danish, please don't ever use machine translators to translate from English. Regardless of what some people may think, they make mistakes, so many mistakes.
I get why it's tempting, good translators are expensive, and few and far between. A friend of my is a professional translator and she's not exactly in need of work, but a lot of customers look at her prices and opt for machine translations instead and the result not always impressive. Errors range from wrong words, bad sentence structure to an inability to correctly translate cultural references.
Right, makes sense for Danes, or other population where English knowledge is basically ubiquitous. But I'm think it might look differently in other places, if the choice is between "Badly translated but I can understand 95% of it" and "In a language I don't understand at all, maybe 1% I could figure out", then the choice might be a bit different.
nope, let the user does the translation, with his own choice of tool and being thus perfectly aware of the shortcomings.
I know that some people translate my French posts to read them. That’s really cool. But I would never post something I didn’t write myself (but I use spellcheking tools. I even sometimes disagree with them)
Not everyone can. Try going to rural Spain and handing out flyers in English and ask them to translate it themselves, 0% of the people will translate it themselves, it'll go straight into the trash. If you instead hand them something in a language they understand, there is a least a chance they'll read it, even though probably 5% will do so.
It's sometimes useful to understand that the world is much bigger and varied than what you experience locally, and what works for you and the people in one country, doesn't always work the same everywhere.
There are levels to things. In a professional context (including product design and documentation/instructions) don‘t use machine translation[†].
For your personal hobby site or for general online communication, you probably shouldn’t use machine translation, but it is probably useful if have B1 language skills and are checking up on your grammar, vocabulary, etc. As for using LLMs to help you write, I certainly prefer people use the traditional models over LLMs, as the traditional models still require you to think and forces you to actually learn more about the output language.
For reading somebody else’s content in a language you don‘t understand, machine translation is fine up to a point, as long as you are aware that it may not be accurate.
---
† In fact I personally I think EU should mandate translator qualification, and probably would have only 20 years ago when consumer protection was still a thing they pretended to care about.
I use Grammarly at work (it's mostly to make sure our brand guidelines are kept) and I don't find that it (defaultly) corrects too far into the ai slop territory. It's mostly just making sure your sentence is correct.
Op is going after AI slop bot farms like android authority
If that's a sole problem, it should be called "Chinese-Japanese-Korean-whateverelse new year" instead. Maybe "East Asian new year" for short. (Not that there are absolutely no discrepancies within them, but they are so similar enough that new year's day almost always coincide.)
This non-problem sounds like it's on the same scale as "The British Isles", a term which is mildly annoying to Irish people but in common use everywhere else.
These metrics necessarily have to underestimate programmer skills because those are not directly controllable. If there is any sort of rigor in these metrics (i.e. I don't know if COCOMO is one of them) they will probably assume, say, a mundane programmer whose performance is worse than 90/95/99% of all other programmers.
Not only this would violate the ToS, but also a newer native version of Claude Code precompiles most JS source files into the JavaScriptCore's internal bytecode format, so reverse engineering would soon become much more annoying if not harder.
What specific parts of the ToS does "sharing different code snippets" violate? Not that I don't believe you, just curious about the specifics as it seems like you've already dug through it.
At least that's much better than not being able to answer them. If LLMs are truly intelligent enough to justify their contributions (including copyrights!), why should we treat them differently from human contributions?
I asked Gemini 3 Pro about the relative difficulty of each project in the list and got the following (parenthesized notes are also by Gemini). Gemini noted that the time estimate is based on the assumption that you already understand the theory (which time estimate would extremely vary anyway) and only accounts for pure PoC implementation and debugging. The numbers look reasonable at my sketchy glance but of course YMMV.
[Difficulty: Low]
42. Twitter Trends 5--10h (If you understand the probabilistic math)
2. Wordle Solver 5--10h (Pure logic/algorithm)
17. BMP Codec 5--10h
23. Auth Server (JWT) 5--10h
24. Autocomplete System 5--10h
66. Browser Extension 5--15h
15. Diff Tool 8--15h (Algorithms heavy)
9. Six Degrees of Kevin Bacon 10--20h (Classic graph problem)
7. Googlebot (Crawler) 10--20h
65. Make 10--20h
[Difficulty: Moderate]
32. Web Server 10--20h
41. Time Sync Daemon (NTP) 10--20h
53. Malware 10--20h
58. Malloc 10--20h
63. Shell 10--20h
19. Quantum Computer Simulation 15--25h (Assuming you know the linear algebra already)
26. Background Noise Remover 15--25h (Math/Signal Processing heavy)
11. Procedural Crosswords 15--25h
39. CDN Caching 15--25h
47. Ray Tracer 15--25h
57. Load Balancer 15--25h
61. CI System 15--25h
62. Random Forest 15--25h
67. Stock Trading Bot 15--25h
56. Lock-Free Data Structures 15--30h (But debugging is painful)
16. Visualize Object-Oriented Code 15--30h (Language parsing is the bottleneck)
5. Container (No Docker) 15--30h (Requires deep Linux systems knowledge)
8. DNS Server 15--30h (Strict RFC compliance required)
70. OpenGL 15--30h
12. Bitcask (KV Store) 20--30h
38. Wikipedia Search 20--30h
50. Amazon Delivery (Vehicle Routing) 20--30h
46. Zip 20--35h (Algorithms heavy)
1. Bittorrent Client 20--40h (Binary parsing and managing async network states)
18. Filesystem (FUSE) 20--40h (Debugging kernel interfaces can be slow)
60. Smart Home 20--40h (Hardware integration eats time)
40. TikTok (Feed) 20--40h (Mostly frontend/UI state complexity)
21. Redis Clone 20--40h
29. Road Network 20--40h
31. Evolutionary Design 20--40h
34. Git 20--40h
59. Netflix (Streaming) 20--40h
69. Automated Journal 20--40h
13. Audio Fingerprinting 25--40h (DSP is sensitive to parameters)
52. Knowledge Graph 25--45h
64. Bitcoin Node 25--45h
14. Dangerous Dave (Game) 30--50h
48. Programming Language 30--50h
[Difficulty: High]
33. Depth Estimation 25--50h (Computer Vision math)
35. GDB (Debugger) 30--50h (Low-level systems programming)
72. Audio Multicast 30--50h (Syncing audio clocks over network is hard)
43. SQL Optimizer 30--50h
36. Neural Networks 30--60h (Debugging gradient calculations is tough)
71. Laser Tag 30--60h (Hardware debugging)
3. Deepfake (Optimal Transport) 30--60h (Math-heavy; debugging matrix operations is difficult)
51. Kafka Broker 30--60h
20. VLC (Video Player) 40--60h (A/V sync drift is very difficult to get right)
28. Google Maps 40--60h
30. Collaborative Editor 40--70h (CRDTs are conceptually dense)
37. Chess 40--70h (Performance optimization is a rabbit hole)
45. VPN 40--70h
27. Dropbox Clone 40--80h (Conflict resolution and sync logic are extremely error-prone)
4. Spreadsheet 40--80h (Cycle detection and UI state management are tricky)
10. RAFT 40--80h (Distributed systems are notoriously hard to debug due to race conditions)
68. Browser Engine 40--80h
73. Decentralized Internet 40--80h
49. Messenger 50--100h
22. Video Editor (Client-side) 50--80h (Browser constraints + heavy compute)
[Difficulty: Very High]
44. Anonymous Voting 40--80h (Cryptography is unforgiving)
6. Geometric Theorem Proving 50--100h+ (Essentially building a symbolic AI engine)
55. TCP/IP Stack 60--100h (TCP state machines are massive)
25. SQLite Clone 60--120h (A database engine combines almost every discipline of CS)
54. Game Boy Advance Emulator 80--150h (Requires extremely precise bit-twiddling and timing)
Maybe we should all adopt Chinese weekday names: Sunday (星期日) remains same, Firstday (星期一) for Monday, Seconday (星期二) for Tuesday, Thirday (星期三) for Wednesday, Fourthday (星期四) for Thursday, Fifthday (星期五) for Friday and Sixthday (星期六) for Saturday. One-letter abbreviations would be simply S, 1 through 6.
Monday - "понедельник", which is coming from the "day after the (previous) week", i.e. after the Sunday
Tuesday - "вторник", true here, has "second" in the name
Wednesday - "среда", has "middle" in the name
Thursday - "четверг", also true, has "fourth" in the name
Friday - "пятница", also true, has "fifth" in the name
Saturday - "суббота", derived from the Hebrew "shabbat"
Sunday - "воскресенье", almost the same word as "воскресение", which is the Christian Church word for the Resurrection (of Jesus Christ)
> All I hear is skill issue. Imagine needing an AI to write stuff.
Grammarly users (and underrepresented non-English speakers) would complain.
reply