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by abernard1
2158 days ago
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> working strings of source code from prompts it (presumably) hasn't seen before I'm saying that "presumably" is wrong, especially on what it was: a simple React program. It would not surprise me if the amount of shared structure and text in the corpus is all over the place. This can be tested by making more and more sophisticated programs in different languages, and seeing how often it returns the correct result. I don't really care, because it can't reliably do basic arithmetic if the numbers are in different ranges. This is dead giveaway it hasn't learned a fundamental structure. If it hasn't learned that, it hasn't learned programming. The examples are not really that impressive either. They are boolean logic. That a model like this can do copy-pasta + encode simple boolean logic and if-else is... well.. underwhelming. Stuff like that has been happening for a long time with these models, and no one has made claims that the models were "reasoning". |
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Also it isn't the case that one needs to be perfect at algorithmic thinking to be capable of some amount of reasoning. I don't claim that GPT-3 is perfect, but that its not just copy and pasting pieces of text it has seen before. It is coming up with new sequences of text based on the structure of the surrounding text and the prompt, in a manner that indicates it has a representation (albeit imperfect) of the semantic properties of the text and can compose them in meaningful ways. Handwavy responses do nothing to undermine the apparent novelty it creates.
>encode simple boolean logic and if-else is... well.. underwhelming. Stuff like that has been happening for a long time with these models, and no one has made claims that the models were "reasoning".
Seems like you're just moving the goalposts as always happens when it comes to AI advances. What do you take to be "reasoning" if that isn't an example of it?