alt Hacker NewsA lot of AI stuff is like that, actually. GPT 2 and 3 were mainly curiosities that would get articles on tech news sites but didn’t attract much attention from the general public. But after RLHF the UX improved dramatically and ChatGPT became mainstream. A lot of MLEs underestimate how much UX matters, and the same is true for Jev.
> how do these models calculate probabilities?
The short answer is: more and better data.
The long answer is: probably the same way any other classifier does. Take your ground truth probabilities and your predicted probabilities. The gap between those is called cross entropy, which is used to push the model towards the correct probabilities.
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> A lot of AI stuff is like that, actually.
Chain of thought was that way. DeepSeek came out, and not long thereafter everyone had adopted chain of thought.
as s.o. who registered their chatgpt account on the third day after they released, I can tell you chatgpt actually became mainstream overnight.
> which is used to push the model towards the correct probabilities.
The definition of "correct probability" here is usually "p=1 for the ground truth label, p=0 for all others." Which seems like an intuitive approach but if you actually think about it doesn't trivially imply the model would learn sensible distributions under uncertainty.