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How long ago would you have considered this discussion ridiculous? How long till GPT-N will be churning out solutions faster than you can read them? It's useles

How long ago would you have considered this discussion ridiculous? How long till GPT-N will be churning out solutions faster than you can read them? It's useless for me now as well, but I'm pretty sure I'll be doomed professionally in the future.

jeffreygoesto 3y ago
Not necessarily. Every hockey stick is just the beginning of an s-curve. It will saturate, probably sooner than you think.
- hackerlight 3y ago
  Some parts of AI will necessarily asymptote to human-level intelligence because of a fixed corpus of training data. It's hard to think AI will become a better creative writer than the best human creative writers, because the AI is trained on their output and you can't go much further than that. But in areas where there's self-play (e.g. Chess, and to a lesser extent, programming), there is no good reason to think it'll saturate, since there isn't a limit on the amount of training data.
  - borissk 3y ago
    So you think human readers have magical powers to rate say a book that an AI can't replicate?
    - hackerlight 3y ago
      There's a gulf of difference between domains where self-play means we have unlimited training data for free (e.g. Chess) versus domains where there's no known way to generate more training data (e.g. Fine art). It's possible that the latter domains will see unpredictable innovations that allow it to generate more training data beyond what humans have produced, but that's an open question.
  - strken 3y ago
    How does programming have self-play? I'm not sure I understand. Are you going to generate leetcode questions with one AI, have another answer them, and have a third determine whether the answer is correct? I'm struggling to understand how an LLM is meant to answer the questions that come up in day-to-day software engineering, like "Why is the blahblah service occasionally timing out? Here are ten bug reports, most of which are wrong or misleading" or "The foo team and bar team want to be able to configure access to a Project based on the sensitivity_rating field using our access control system, so go and talk to them about implementing ABAC". The discipline of programming might be just a subset of broader software engineering, but it arguably still contains debugging, architecture, and questions which need more context than you can feed into an LLM now. Can't really self-play those things without interacting with the real world.
    - hackerlight 3y ago
      > How does programming have self-play? I think there's potentially ways to generate training data, since success can be quantified objectively, e.g. if a piece of generated code compiles and generates a particular result at runtime, then you have a way to discriminate outcomes without a human in the loop. It's in the grey area between pure self-play domains (e.g. chess) and domains that are more obviously constrained by the corpus of data that humans have produced (e.g. fine art). Overall it's probably closer to the latter than the former.
  - voitvod 3y ago
    This is totally wrong. It has already saturated because we are already using all the data we can. The language model "creativity" is a total fraud. It is not creative at all but it takes time to see the edges. It is like AI art. AI art is mind blowing until you have seen the same 2000th variation on basically the same theme because it is so limited in what it can do. To compare the simple game of chess to the entire space of what can be programmed on a computer is utterly absurd. You just don't know what you are talking about.

jeffreygoesto 3y ago

Not necessarily. Every hockey stick is just the beginning of an s-curve. It will saturate, probably sooner than you think.

hackerlight 3y ago
Some parts of AI will necessarily asymptote to human-level intelligence because of a fixed corpus of training data. It's hard to think AI will become a better creative writer than the best human creative writers, because the AI is trained on their output and you can't go much further than that. But in areas where there's self-play (e.g. Chess, and to a lesser extent, programming), there is no good reason to think it'll saturate, since there isn't a limit on the amount of training data.
- borissk 3y ago
  So you think human readers have magical powers to rate say a book that an AI can't replicate?
  - hackerlight 3y ago
    There's a gulf of difference between domains where self-play means we have unlimited training data for free (e.g. Chess) versus domains where there's no known way to generate more training data (e.g. Fine art). It's possible that the latter domains will see unpredictable innovations that allow it to generate more training data beyond what humans have produced, but that's an open question.
- strken 3y ago
  How does programming have self-play? I'm not sure I understand. Are you going to generate leetcode questions with one AI, have another answer them, and have a third determine whether the answer is correct? I'm struggling to understand how an LLM is meant to answer the questions that come up in day-to-day software engineering, like "Why is the blahblah service occasionally timing out? Here are ten bug reports, most of which are wrong or misleading" or "The foo team and bar team want to be able to configure access to a Project based on the sensitivity_rating field using our access control system, so go and talk to them about implementing ABAC". The discipline of programming might be just a subset of broader software engineering, but it arguably still contains debugging, architecture, and questions which need more context than you can feed into an LLM now. Can't really self-play those things without interacting with the real world.
  - hackerlight 3y ago
    > How does programming have self-play? I think there's potentially ways to generate training data, since success can be quantified objectively, e.g. if a piece of generated code compiles and generates a particular result at runtime, then you have a way to discriminate outcomes without a human in the loop. It's in the grey area between pure self-play domains (e.g. chess) and domains that are more obviously constrained by the corpus of data that humans have produced (e.g. fine art). Overall it's probably closer to the latter than the former.
- voitvod 3y ago
  This is totally wrong. It has already saturated because we are already using all the data we can. The language model "creativity" is a total fraud. It is not creative at all but it takes time to see the edges. It is like AI art. AI art is mind blowing until you have seen the same 2000th variation on basically the same theme because it is so limited in what it can do. To compare the simple game of chess to the entire space of what can be programmed on a computer is utterly absurd. You just don't know what you are talking about.