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I see, thanks. I guess it means that if there was only a statistical model of [moves]->[next move], this would be impossible (or extremely unlikely) to work.
by the_gipsy 4y ago
I see, thanks. I guess it means that if there was only a statistical model of [moves]->[next move], this would be impossible (or extremely unlikely) to work.
- IanCal 4y agoYeah, exactly. I think it's a really interesting approach to answering the question of what these things might be doing. You can still try and frame it as some overall statistical model of moves -> next move (I think there's discussions on this in the comments that I don't fancy getting into) but I think the paper does a good job of discussing this in terms of surface statistics: > From various philosophical [1] and mathematical [2] perspectives, some researchers argue that it is fundamentally impossible for models trained with guess-the-next-word to learn the “meanings'' of language and their performance is merely the result of memorizing “surface statistics”, i.e., a long list of correlations that do not reflect a causal model of the process generating the sequence. On the other side, it's reasonable to think that these models can learn a model of the world but don't necessarily do so. And sufficiently advanced surface statistics will look very much like an agent with a model of the world until it does something catastrophically stupid. To be fair to the models, I do the same thing. I have good models of some things and others I just perform known-good actions and it seems to get me by.