alt Hacker NewsThis. By now I don’t understand how anyone can still argue in the abstract while it’s trivial to simply give it a try and collect cold, hard facts.
It’s like arguing that the piano in the room is out of tune and not bothering to walk over to the piano and hit its keys.
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It's like arguing that the piano goes out of tune randomly and that even if you get through 1, 2, or even 10 songs without that happening, I'm not interested in playing that piano on stage.
So I tried it and it is worse that having random dude from Fiverr write you code — it is actively malicious and goes out of it's way do decieve and to subtly sabotage existing working code.
Do I now get the right to talk badly about all LLM coding, or is there another exercise I need to take?
I am hitting the keys, and I call bullshit.
Yes, the technology is interesting and useful. No, it is not a “10x” miracle.
Downside is a lot of those that argue, try out some stuff in ChatGPT or other chat interface without digging a bit further. Expecting "general AI" and asking general questions where LLMs are most prone for hallucinations. Other part is cheap out setups using same subscription for multiple people who get history polluted.
They don't have time to check more stuff as they are busy with their life.
People who did check the stuff don't have time in life to prove to the ones that argue "in exactly whatever the person arguing would find useful way".
Personally like a year ago I was the person who tried out some ChatGPT and didn't have time to dabble, because all the hype was off putting and of course I was finding more important and interesting things to do in my life besides chatting with some silly bot that I can trick easily with trick questions or consider it not useful because it hallucinated something I wanted in a script.
I did take a plunge for really a deep dive into AI around April last year and I saw for my own eyes ... and only that convinced me. Using API where I built my own agent loop, getting details from images, pdf files, iterating on the code, getting unstructured "human" input into structured output I can handle in my programs.
*Data classification is easy for LLM. Data transformation is a bit harder but still great. Creating new data is hard so like answering questions where it has to generate stuff from thin air it will hallucinate like a mad man.*
Data classification like "is it a cat, answer with yes or no" it will be hard for latest models to start hallucinating.