6 ms·

> the idea that larger models can do more than smaller models, which should be a surprise to no one. Actually this was quite a surprise to a lot of people, sin

> the idea that larger models can do more than smaller models, which should be a surprise to no one. Actually this was quite a surprise to a lot of people, since the whole race to scaling up began, with GPT2 or so. It was totally not obvious that you can scale up the model (and also training) and it would improve the performance. Many (most?) people thought there would be some limit, and we were close to that limit with 100M-500M params or so. Then GPT2 came. And it was a surprise to a lot of people, that scaling up works so well. But then the question remained, is the limit reached now, or not, or is there any? The scaling laws appeared, and seemed to indicate that there really is no limit. Still, GPT3 and then GPT4 were still surprising to people, that it really got better and better. But the question still remains, is there a limit? If there is no limit, it means we can easily surpass human intelligence by just scaling up further. Maybe the limit is just always current technical hardware limitations and cost.

kerkeslager 3y ago
You didn't read the post you're responding to, and shouldn't be responding. In fact, you didn't read the part of the post you quoted, where I said it should be a surprise to no one. But, unsurprisingly, the sort of people who stop reading at the first chance they see to correct something, are easily surprised, since actually understanding LLMs would require actually doing some nuanced reading.
- pmoriarty 3y ago
  Please consider HN's Guidelines[1] when replying. In particular: - Please don't comment on whether someone read an article. "Did you even read the article? It mentions that" can be shortened to "The article mentions that". - Be kind. Don't be snarky. Converse curiously; don't cross-examine. Edit out swipes. - Please don't fulminate. Please don't sneer, including at the rest of the community. [1] - https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html
  - kerkeslager 3y ago
    > Please don't comment on whether someone read an article. "Did you even read the article? It mentions that" can be shortened to "The article mentions that". This guideline is likely one of the main reasons Hacker News comments are so simultaneously overconfident and undereducated. If you want HN to be a safe place for people interrupting informed conversation with whatever nonsense pops into their head, fine, but I don't want that, and until that guideline becomes a rule, I'm not going to be following it. People should read what they're responding to before responding. Note, in this case, it's objectively clear that the person did not read my post--I put something in my post to prove that fact. This isn't just snark. > Be kind. Don't be snarky. Converse curiously; don't cross-examine. Edit out swipes. Is it kind to jump in at the first opportunity to correct someone without reading what they've said? Is it kind to spread misinformation that causes societal harm? This is a very shallow idea of kindness.
    - mustacheemperor 3y ago
      It seems that commenter did in fact read the article, so I for one as someone far less informed than both of you am interested to see the discussion carry on. On that note, >Please respond to the strongest plausible interpretation of what someone says, not a weaker one that's easier to criticize. Assume good faith. “You didn’t even read it” is not the strongest plausible interpretation of that reply nor assumes good faith.
      - kerkeslager 3y ago
        > “You didn’t even read it” is not the strongest plausible interpretation of that reply nor assumes good faith. Really? Did you read the last paragraph of my post that they were responding to? Can you explain that?
        deleted 3y ago
        [deleted]
        jrmg 3y ago
- albertzeyer 3y ago
  I think you are misunderstanding sth. I did read your post. I'm also publishing peer-reviewed research articles related to this. I think I have some good understanding on this. I was simply saying that I partly disagree with you. And I still do. It's wrong that this should be a surprise to no-one. In fact, I think it is reasonable that it is surprising. It was indeed really unexpected that scaling up such models leads to such behavior. Now that we have such models, and see this behavior, sure you can say in hindsight, of course it's obvious, nothing unexpected. But this is wrong. It was unexpected to many people. And saying "it should not have been unexpected", I'm not really sure what you want to say with that. Yes, it would be nice if everyone's prediction are always correct. Obviously that's not the case. Or you are saying you think this is a particular trivial case. I would disagree. English is not my native language. Maybe I just understood sth wrong.
  - cubefox 3y ago
    One of the few people who publicly predicted the amazing abilities of the GPT-2 successors was Scott Alexander: https://slatestarcodex.com/2019/02/19/gpt-2-as-step-toward-general-intelligence/ https://slatestarcodex.com/2019/02/19/gpt-2-as-step-toward-g... There may have been others who expected similar miracles, but there certainly weren't many. We can conclude that at least GPT-3 took most by surprise. (I don't know how many people even knew about GPT before GPT-2 came out, it's probably hard to get a sample.) Heck, even the vast majority of people here on HN wasn't much interested in GPT-3 before ChatGPT, their new cheaper API prices, and GPT-4 came out. And when we talk about "normal people", they didn't know GPT-3 at all, they only noticed Dall-E 2, somewhat, and finally were caught by surprise when word about ChatGPT spread in a matter of weeks.
  - fzeroracer 3y ago
    I recommend rereading the last line of his post. I think it's overly aggro, but you did not read his post since you ignored the very last line of it.
    - deleted 3y ago
      [deleted]
    - 3y ago
cubefox 3y ago
The limit of LLMs becomes clear when we consider how they work. They gain their abilities from imitation learning. They imitate human text. This could get them to Wikipedia level intelligence (or knowledge), which might be somewhat superhuman, but not much further. To really go beyond human intelligence, you'd need a system which isn't constrained by imitating text. In fact, animal brains probably work by predicting sensory experiences (predictive coding), which are a function of reality. Unlike predicting text, which is a function of human ability.

kerkeslager 3y ago

You didn't read the post you're responding to, and shouldn't be responding. In fact, you didn't read the part of the post you quoted, where I said it should be a surprise to no one. But, unsurprisingly, the sort of people who stop reading at the first chance they see to correct something, are easily surprised, since actually understanding LLMs would require actually doing some nuanced reading.

pmoriarty 3y ago
Please consider HN's Guidelines[1] when replying. In particular: - Please don't comment on whether someone read an article. "Did you even read the article? It mentions that" can be shortened to "The article mentions that". - Be kind. Don't be snarky. Converse curiously; don't cross-examine. Edit out swipes. - Please don't fulminate. Please don't sneer, including at the rest of the community. [1] - https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html
- kerkeslager 3y ago
  > Please don't comment on whether someone read an article. "Did you even read the article? It mentions that" can be shortened to "The article mentions that". This guideline is likely one of the main reasons Hacker News comments are so simultaneously overconfident and undereducated. If you want HN to be a safe place for people interrupting informed conversation with whatever nonsense pops into their head, fine, but I don't want that, and until that guideline becomes a rule, I'm not going to be following it. People should read what they're responding to before responding. Note, in this case, it's objectively clear that the person did not read my post--I put something in my post to prove that fact. This isn't just snark. > Be kind. Don't be snarky. Converse curiously; don't cross-examine. Edit out swipes. Is it kind to jump in at the first opportunity to correct someone without reading what they've said? Is it kind to spread misinformation that causes societal harm? This is a very shallow idea of kindness.
  - mustacheemperor 3y ago
    It seems that commenter did in fact read the article, so I for one as someone far less informed than both of you am interested to see the discussion carry on. On that note, >Please respond to the strongest plausible interpretation of what someone says, not a weaker one that's easier to criticize. Assume good faith. “You didn’t even read it” is not the strongest plausible interpretation of that reply nor assumes good faith.
    - kerkeslager 3y ago
      > “You didn’t even read it” is not the strongest plausible interpretation of that reply nor assumes good faith. Really? Did you read the last paragraph of my post that they were responding to? Can you explain that?
      - deleted 3y ago
        [deleted]
      - jrmg 3y ago
albertzeyer 3y ago
I think you are misunderstanding sth. I did read your post. I'm also publishing peer-reviewed research articles related to this. I think I have some good understanding on this. I was simply saying that I partly disagree with you. And I still do. It's wrong that this should be a surprise to no-one. In fact, I think it is reasonable that it is surprising. It was indeed really unexpected that scaling up such models leads to such behavior. Now that we have such models, and see this behavior, sure you can say in hindsight, of course it's obvious, nothing unexpected. But this is wrong. It was unexpected to many people. And saying "it should not have been unexpected", I'm not really sure what you want to say with that. Yes, it would be nice if everyone's prediction are always correct. Obviously that's not the case. Or you are saying you think this is a particular trivial case. I would disagree. English is not my native language. Maybe I just understood sth wrong.
- cubefox 3y ago
  One of the few people who publicly predicted the amazing abilities of the GPT-2 successors was Scott Alexander: https://slatestarcodex.com/2019/02/19/gpt-2-as-step-toward-general-intelligence/ https://slatestarcodex.com/2019/02/19/gpt-2-as-step-toward-g... There may have been others who expected similar miracles, but there certainly weren't many. We can conclude that at least GPT-3 took most by surprise. (I don't know how many people even knew about GPT before GPT-2 came out, it's probably hard to get a sample.) Heck, even the vast majority of people here on HN wasn't much interested in GPT-3 before ChatGPT, their new cheaper API prices, and GPT-4 came out. And when we talk about "normal people", they didn't know GPT-3 at all, they only noticed Dall-E 2, somewhat, and finally were caught by surprise when word about ChatGPT spread in a matter of weeks.
- fzeroracer 3y ago
  I recommend rereading the last line of his post. I think it's overly aggro, but you did not read his post since you ignored the very last line of it.
  - deleted 3y ago
    [deleted]
  - 3y ago

cubefox 3y ago

The limit of LLMs becomes clear when we consider how they work. They gain their abilities from imitation learning. They imitate human text. This could get them to Wikipedia level intelligence (or knowledge), which might be somewhat superhuman, but not much further. To really go beyond human intelligence, you'd need a system which isn't constrained by imitating text. In fact, animal brains probably work by predicting sensory experiences (predictive coding), which are a function of reality. Unlike predicting text, which is a function of human ability.