10 ms·

It is hard for me to relate to comments like this. It is like we aren't using the same tool? GPT-4 is nothing short of amazing. Early GPT-3.5 before it was cl

It is hard for me to relate to comments like this. It is like we aren't using the same tool? GPT-4 is nothing short of amazing. Early GPT-3.5 before it was clamped down also was _much_ less boring until it had be RLHF'd into the ground for "safety" and political risk. I admit that the major models (GPT-4 and Claude) have been censored into the ground. But even with that, it is a supremely useful tool. I've piped complete garbage data into it and asked for structured output, and I get flawless results almost every time. It is a huge time saver on such a large axis of tasks. These LLMs feel like the next "UI" paradigm to modern computing, and I just don't get how people can be cynical about it. Ignore the hype bros and VC peddlers, but don't throw the baby out with the bath water.

School-Cotton 3y ago
I suspect most people who say stuff like the comment you responded to have simply not tried 4.
andy99 3y ago
I don't agree with everything but I certainly relate to the comment. > That's the tell-tale sign of LLM content: zero substance and boring prose. This is absolutely true. With the right constraints you can get some good answers (and many more parlor tricks as mentioned). Left to their own devices like answering vague questions or on longer answers, llms including GPT4 generate empty substanceless drivel. Doesn't make it worthless, definitely makes it overhyped.
- lacrimacida 3y ago
  How could vague questions be rewarded with any substance? Im sure that could be baked in somehow but one still has to pick their type of substance otherwise it’s too broad to make any sense. But substance really isn’t their goal, tools don’t provide any of that and LLMs aren’t anything else but a tool. There is a lot of hype, I agree, but that doesn’t mean LLMs aren’t useful and it’s all hype.
- pyinstallwoes 3y ago
  So most university papers?
- drakenot 3y ago
  > On two occasions I have been asked [by members of Parliament], 'Pray, Mr. Babbage, if you put into the machine wrong figures, will the right answers come out?' I am not able rightly to apprehend the kind of confusion of ideas that could provoke such a question.
  - girvo 3y ago
    Though LLMs now have fun examples of giving the wrong answers to the right questions, too. That's a neat evolution!
girvo 3y ago
> I've piped complete garbage data into it and asked for structured output, and I get flawless results almost every time This must truly be a skill issue on my end, because that is not my experience
- dvt 3y ago
  It's typical AI cope. Every time I ask for a specific example that does something mind-blowing (whether it's Copilot or ChatGPT, or whatever), it's always ignored. I've tried using both ChatGPT and Copilot for coding. Other than generating the most basic of boilerplate, it's completely garbage. I've tried parsing unstructured data. Unless it's trivial to parse, it's full of errors (in some cases hallucinations). And when I bring this up, it's always followed up with "we're early bro, AI will get better bro, trust me bro, just a few more terabytes of training data bro."
  - School-Cotton 3y ago
    Are you using 3.5 or 4? It makes a gigantic difference.

School-Cotton 3y ago

I suspect most people who say stuff like the comment you responded to have simply not tried 4.

andy99 3y ago

I don't agree with everything but I certainly relate to the comment. > That's the tell-tale sign of LLM content: zero substance and boring prose. This is absolutely true. With the right constraints you can get some good answers (and many more parlor tricks as mentioned). Left to their own devices like answering vague questions or on longer answers, llms including GPT4 generate empty substanceless drivel. Doesn't make it worthless, definitely makes it overhyped.

lacrimacida 3y ago
How could vague questions be rewarded with any substance? Im sure that could be baked in somehow but one still has to pick their type of substance otherwise it’s too broad to make any sense. But substance really isn’t their goal, tools don’t provide any of that and LLMs aren’t anything else but a tool. There is a lot of hype, I agree, but that doesn’t mean LLMs aren’t useful and it’s all hype.
pyinstallwoes 3y ago
So most university papers?
drakenot 3y ago
> On two occasions I have been asked [by members of Parliament], 'Pray, Mr. Babbage, if you put into the machine wrong figures, will the right answers come out?' I am not able rightly to apprehend the kind of confusion of ideas that could provoke such a question.
- girvo 3y ago
  Though LLMs now have fun examples of giving the wrong answers to the right questions, too. That's a neat evolution!

girvo 3y ago

> I've piped complete garbage data into it and asked for structured output, and I get flawless results almost every time This must truly be a skill issue on my end, because that is not my experience

dvt 3y ago
It's typical AI cope. Every time I ask for a specific example that does something mind-blowing (whether it's Copilot or ChatGPT, or whatever), it's always ignored. I've tried using both ChatGPT and Copilot for coding. Other than generating the most basic of boilerplate, it's completely garbage. I've tried parsing unstructured data. Unless it's trivial to parse, it's full of errors (in some cases hallucinations). And when I bring this up, it's always followed up with "we're early bro, AI will get better bro, trust me bro, just a few more terabytes of training data bro."
- School-Cotton 3y ago
  Are you using 3.5 or 4? It makes a gigantic difference.