Sure but what's being advertised isn't sentience per se, at least with the leetcode part of their benchmarks. The issue here is that they claim that it can do X% on leetcode, but it seems like it's much less on new data. Even if it learned to find previous solutions and replace it with changes it should be able to perform well due to the nature of the problems.

Yeah but if you were to come up with a problem in your head that didn't exist word for word then GPT-4 would be doing what they're advertising, however, if the problem was word for word anywhere in the training data then the testing data is contaminated. If the model can learn the design patterns for leetcode style questions by looking at examples of them, then it's doing something really good, if it can only solve problems that it has seen before, then it's nothing special, they just overfit a trillion parameters on a comparatively very small dataset.

This sub is over, it's been taken over by users and startups trying to promote their own products rather than researchers.

The other day I (mobile) searched for something related to meme stocks and the pills under the search bar showed the News followed by a button that said (+ Reddit), I clicked it and it literally just added reddit to my search term.

You're deluded if you don't think SEO doesn't exist in a worse way for LLMs, there's tons of papers about that, you can just mine for phrases that increases likelihoods just by observing outputs.

Pytorch supports it but there's still some bugs here and there, you might also find that a function or its gradient isn't implemented yet on some architectures.