Re:Do we understand how neural networks work?
by SEGyges on Thursday August 14, 2025 @04:07AM
(#44897972)
My short explanation would be that even for RL, you are training on a next token objective; but the next token is something that has been selected very very carefully for solving the problem, and was generated by the model itself.
So you're amplifying existing trajectories in the model by feeding the model's outputs back to itself, but only when those outputs solve a problem.
This elides the kl penalty and the odd group scoring, which are the same in the limit but vastly more efficient in practice.
Re:Do we understand how neural networks work?
by astrange on Thursday August 14, 2025 @04:27AM
(#44898116)
Inference often isn't next token prediction though, either weakly (because of speculative decoding/multiple token outputs) or strongly (because of tool usage like web search).
Re:Do we understand how neural networks work?
by porridgeraisin on Thursday August 14, 2025 @07:37AM
(#44899208)
Well I may be misunderstanfing you, but speculative decoding is just using next token predictions from a few models(or many samples from one model) instead of just one sample. It is still next token prediction.
Tool usage is also just next token prediction. You have it predict the next token of the syntax needed for tool use, and then it is fed the result of that in context which it then predicts the next token of.
Re:Do we understand how neural networks work?
by astrange on Thursday August 14, 2025 @08:03AM
(#44899413)
The text returned by the tool itself makes it not "next token prediction". Aside from having side effects, the reason it's helpful is that it's out of distribution for the model. So it changes the properties of the system.
Re:Do we understand how neural networks work?
by porridgeraisin on Thursday August 14, 2025 @08:12AM
(#44899466)
Ah ok, understood what you meant.
Policy gradient approaches in RL are just supervised learning, when viewed through some lenses. You can search for karpathys more fleshed out argument for the same, I'm on mobile jow.