4 ms·

"Complex and multifaceted" sounds like freshman gobbledygook and any serious reader would inquire: complex how? Multifaceted how? "...have begun a unstoppable

by dvt 3y ago

"Complex and multifaceted" sounds like freshman gobbledygook and any serious reader would inquire: complex how? Multifaceted how? "...have begun a unstoppable chain of incestuous linguistic evolution"—I disagree with this, I don't really think anyone takes ChatGPT (other than the Kool-Aid drinkers and VC peddlers) to be anything more than a parlor trick. A modern Schachtürke that will soon be overshadowed by the next shiny ball. Even OpenAI's user base has plummeted. The content it generates isn't merely often wrong, or nonsensical, or overly-sanitized, it's simply boring. That's the tell-tale sign of LLM content: zero substance and boring prose.

drakenot 3y ago
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.
actionfromafar 3y ago
But don’t you think LLMs will affect how people write and by extension how they even talk, and think? That will be fed back into the next LLM or whatever we will call it. Radio, and later TV, immensely affected language, I think it’s safe to say the LLM will, too.
- orbital-decay 3y ago
  Don't you think everything affects how people write and by extension how they even talk, and think? The world changes all the time, and the culture changes with it. >That will be fed back into the next LLM or whatever we will call it. Large models are already "contaminated" by the output of other models, or even by previous versions of the same model. That's how their enormous datasets are bootstrapped in the first place - it's impossible without automation. That doesn't matter much; what matters is manual curation during the training and mixing in the data from the real world to keep the model in check. Same as with humans and our intelligence distilled over generations, basically.
  - actionfromafar 3y ago
    Yes.

by dvt 3y ago

drakenot 3y ago

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.

actionfromafar 3y ago

But don’t you think LLMs will affect how people write and by extension how they even talk, and think? That will be fed back into the next LLM or whatever we will call it. Radio, and later TV, immensely affected language, I think it’s safe to say the LLM will, too.

orbital-decay 3y ago
Don't you think everything affects how people write and by extension how they even talk, and think? The world changes all the time, and the culture changes with it. >That will be fed back into the next LLM or whatever we will call it. Large models are already "contaminated" by the output of other models, or even by previous versions of the same model. That's how their enormous datasets are bootstrapped in the first place - it's impossible without automation. That doesn't matter much; what matters is manual curation during the training and mixing in the data from the real world to keep the model in check. Same as with humans and our intelligence distilled over generations, basically.
- actionfromafar 3y ago
  Yes.