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I think you've fallen into the trap of "AIs don't generalize, they memorize." But they do in fact generalize. The reason ChatGPT is so valuable is precisely bec

I think you've fallen into the trap of "AIs don't generalize, they memorize." But they do in fact generalize. The reason ChatGPT is so valuable is precisely because it can help out with situations that have never been seen before, not because it merely unlocks old preexisting knowledge. The fella who saved their dog with ChatGPT comes to mind. https://nypost.com/2023/03/27/chatgpt-saved-my-dogs-life-after-vet-couldnt-diagnosis-it/ https://nypost.com/2023/03/27/chatgpt-saved-my-dogs-life-aft...

bob1029 3y ago
> I think you've fallen into the trap of "AIs don't generalize, they memorize." Binary classifiers don't generalize? Just because my output is not generative does not mean we are cannot learn / generalize elsewhere. Think of it as a 2-stage process.
Zircom 3y ago
Did you read the article you posted? -ChatGPT initially gives the same diagnosis the vets did, Babesiosis -It notes that Babesiosis may have either been a misdiagnosis or there may be a secondary condition/infection causing the remaining symptoms after the Babesiosis treatment didn't resolve all of them -It suggests such a hypothetical secondary condition could be IMHA, which the article notes is an extremely common complication of Babesiosis with this specific dog breed -A quick Google search brings up a fair amount of literature about the association between Babesiosis and IMHA So in fact this is the opposite of a never before seen situation, ChatGPT was just regurgitating common comorbidities of Babesiosis and the vets in question are terrible at their job.
- sillysaurusx 3y ago
  Are you suggesting that it was commonplace for machine learning models to be able to extrapolate medical case reports into an actual diagnosis? Even being able to read and understand a case report is a minor miracle in extrapolation, and it’s interesting how far the goal posts move.
  - lossolo 3y ago
    I have another example of ChatGPT not generalizing but just being a really good statistical model. I needed a solution to a problem that you can't find on Google, and a variation of a problem that also can't be found on Google. I attempted to obtain around 15 lines of code from ChatGPT that would solve the problem, but it consistently failed to produce the correct solution. I spent a few hours trying different prompts, indicating its errors and receiving apologies, only for it to generate another incorrect solution while acknowledging its mistake. Solving out of distribution problems correctly seems almost impossible for it.
    - sillysaurusx 3y ago
      GPT 3.5 or 4? Surprisingly it makes a huge difference. I think a lot of peoples’ impressions are with 3.5, but many startups couldn’t have been built on it, whereas with 4 they can. If it was 4 I’d be curious about the specific problem if you’d be willing to link to the chat.
      - avereveard 3y ago
        I had similar issue with gpt4, was looking for a library that given a grammar and a string, would produce a list of next valid symbols. Gpt4 only ever suggested grammar validator to the point I had given up and was going to write a grammar generator, and so I started looking for the equivalent of antlr in python, and in three searches I find out nltk.grammar that actually solves the original problem It's not a new library either, so I'm dumbfounded by why gpt4 couldn't make sense of my request.
        disgruntledphd2 3y ago
        If it hasn't been used much/talked about much for this purpose then you wouldn't expect it to, right?
        avereveard 3y ago
        true, but then it's neither interpolating between the public documentation nor extrapolating from the possible similarities between concepts
PheonixPharts 3y ago
I think you have fallen into the trap of mistaking interpolation for generalization. Working with these models every day, it's clear that they can certainly interpolate between points in latent space and generate sensible answers to unseen questions, but it's pretty clear that they don't generalize. I've seen far to many examples of models failing to display any sense of generalization to believe otherwise. That's not to say that interpolation in a rich latent space of text isn't very useful. But it's not the same level of abstraction that comes from true generalization in this space.
- riwsky 3y ago
  I think we’ve all fallen into the trap of mistaking pithiness for evidence
- famouswaffles 3y ago
  >it's pretty clear that they don't generalize. I've seen far to many examples of models failing to display any sense of generalization to believe otherwise Failing to generalize on whatever you have in mind is not evidence that the models are incapable of generalization. If you really think so, just be prepared to write off a good chunk of humans as well lol. This is generalization. https://general-pattern-machines.github.io/ https://general-pattern-machines.github.io/ Just seems to me like you've taken examples of generalization and invented an alternate meaning just so you can't admit it generalizes. "Oh but you see this example of answering an unseen question is "insert meaningless distinction" so it doesn't really count"
- johndough 3y ago
  With a sufficiently large dataset, every problem becomes interpolation.
- nl 3y ago
  Given a multi-dimensional latent space with enough dimensions it's hard to imagine cases of generalization that aren't interpolation between points in latent space (given enough data). The one possible exception is logical inference, and this problem seems tractable with tool use or programming.
mejutoco 3y ago
> With ChatGPT, you cannot realistically explain why you got some output in a way that anyone other than an AI/ML expert would find satisfying IMHO OP is talking about "explainability" of the results, which is notoriously bad for current AI. For certain applications (idk if SQL would be one but mortgage application might be one) it is required to be able to explain how the computer got to the decision.

bob1029 3y ago

> I think you've fallen into the trap of "AIs don't generalize, they memorize." Binary classifiers don't generalize? Just because my output is not generative does not mean we are cannot learn / generalize elsewhere. Think of it as a 2-stage process.

Zircom 3y ago

Did you read the article you posted? -ChatGPT initially gives the same diagnosis the vets did, Babesiosis -It notes that Babesiosis may have either been a misdiagnosis or there may be a secondary condition/infection causing the remaining symptoms after the Babesiosis treatment didn't resolve all of them -It suggests such a hypothetical secondary condition could be IMHA, which the article notes is an extremely common complication of Babesiosis with this specific dog breed -A quick Google search brings up a fair amount of literature about the association between Babesiosis and IMHA So in fact this is the opposite of a never before seen situation, ChatGPT was just regurgitating common comorbidities of Babesiosis and the vets in question are terrible at their job.

sillysaurusx 3y ago
Are you suggesting that it was commonplace for machine learning models to be able to extrapolate medical case reports into an actual diagnosis? Even being able to read and understand a case report is a minor miracle in extrapolation, and it’s interesting how far the goal posts move.
- lossolo 3y ago
  I have another example of ChatGPT not generalizing but just being a really good statistical model. I needed a solution to a problem that you can't find on Google, and a variation of a problem that also can't be found on Google. I attempted to obtain around 15 lines of code from ChatGPT that would solve the problem, but it consistently failed to produce the correct solution. I spent a few hours trying different prompts, indicating its errors and receiving apologies, only for it to generate another incorrect solution while acknowledging its mistake. Solving out of distribution problems correctly seems almost impossible for it.
  - sillysaurusx 3y ago
    GPT 3.5 or 4? Surprisingly it makes a huge difference. I think a lot of peoples’ impressions are with 3.5, but many startups couldn’t have been built on it, whereas with 4 they can. If it was 4 I’d be curious about the specific problem if you’d be willing to link to the chat.
    - avereveard 3y ago
      I had similar issue with gpt4, was looking for a library that given a grammar and a string, would produce a list of next valid symbols. Gpt4 only ever suggested grammar validator to the point I had given up and was going to write a grammar generator, and so I started looking for the equivalent of antlr in python, and in three searches I find out nltk.grammar that actually solves the original problem It's not a new library either, so I'm dumbfounded by why gpt4 couldn't make sense of my request.
      - disgruntledphd2 3y ago
        If it hasn't been used much/talked about much for this purpose then you wouldn't expect it to, right?
        avereveard 3y ago
        true, but then it's neither interpolating between the public documentation nor extrapolating from the possible similarities between concepts

PheonixPharts 3y ago

I think you have fallen into the trap of mistaking interpolation for generalization. Working with these models every day, it's clear that they can certainly interpolate between points in latent space and generate sensible answers to unseen questions, but it's pretty clear that they don't generalize. I've seen far to many examples of models failing to display any sense of generalization to believe otherwise. That's not to say that interpolation in a rich latent space of text isn't very useful. But it's not the same level of abstraction that comes from true generalization in this space.

riwsky 3y ago
I think we’ve all fallen into the trap of mistaking pithiness for evidence
famouswaffles 3y ago
>it's pretty clear that they don't generalize. I've seen far to many examples of models failing to display any sense of generalization to believe otherwise Failing to generalize on whatever you have in mind is not evidence that the models are incapable of generalization. If you really think so, just be prepared to write off a good chunk of humans as well lol. This is generalization. https://general-pattern-machines.github.io/ https://general-pattern-machines.github.io/ Just seems to me like you've taken examples of generalization and invented an alternate meaning just so you can't admit it generalizes. "Oh but you see this example of answering an unseen question is "insert meaningless distinction" so it doesn't really count"
johndough 3y ago
With a sufficiently large dataset, every problem becomes interpolation.
nl 3y ago
Given a multi-dimensional latent space with enough dimensions it's hard to imagine cases of generalization that aren't interpolation between points in latent space (given enough data). The one possible exception is logical inference, and this problem seems tractable with tool use or programming.

mejutoco 3y ago

> With ChatGPT, you cannot realistically explain why you got some output in a way that anyone other than an AI/ML expert would find satisfying IMHO OP is talking about "explainability" of the results, which is notoriously bad for current AI. For certain applications (idk if SQL would be one but mortgage application might be one) it is required to be able to explain how the computer got to the decision.