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▲ walrus01 an hour ago

I'm not anthropomorphizing anything, I literally said that the training data for the formulas and equations is baked into it. It only "knows" things because a crawler and scraper acquired the information from an existing written source. In just about the same way that information is baked into a printed encyclopedia.

▲hodgehog11 an hour ago | parent | next [-]

This is not even remotely accurate. "Baking information" like into a "printed encyclopedia" is memorization. It has been shown, time and time again, that LLMs do not merely memorize. It is not even possible for it to do so at scale. It can memorize some things, yes, but it is forced during the training procedure to bake general concepts into intermediate layers (this is why transfer learning works), analogous to compression. One can make several arguments that compression and intrinisic feature sparsity is the closest mathematical explanation to understanding that we have.

▲astrange an hour ago | parent | prev [-]

No, most of a modern LLM's training time is spent in RLVR, which does not "acquire information from an existing source". You can RL behaviors into a randomly initialized neural network.

▲hodgehog11 an hour ago | parent [-]

This is true, but you're not going to get anywhere. The pretraining phase is necessary to immensely reduce variance in the RLVR stage. Once there, RLVR has a surprising tendency to only restrict the generated space further. This is not true of RLHF, by the way, which I find to be particularly fascinating, but I digress.