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Published podcast speaker
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5 transcript-backed records
01 / evaluation
“1 of the reasons why we like sudoku is it's very easy to scan a row, scan a column, and scan a little 3 by 3 box so it fits with how we can address that data structure, if you will.”
02 / evaluation
“I think what's fascinating is that that real world structure seems very hard to mathematize.”
03 / evaluation
“Because, actually, formal logic is not something that we're built to do. So I guess I I expect I expect these systems to once they can really play with all of these modules, including ones that we don't have, like visualizing things in 7 dimensions, they'll be able to do a lot just as when they start I'm not sure if we should do this, but when we give them access to 3 d printers and fab labs so that they can start building things and seeing whether they work, well, maybe we should solve the alignment problem first.”
04 / evaluation
“Turing machines as an architecture, I think, are rather brittle. And, I mean, I think that the partly analog nature of neural networks and, and LLMs, this ability to, I mean, I know that they can be made discrete and so on, but somehow their ability to work in a continuous way with high dimensional vector spaces and embeddings, I I think that that is important to their trainability, even if it's not ultimately important to their cognitive abilities.”
05 / evaluation
“I mean, I don't think that at the fundamental level things are cellular automata because I think that doesn't really work with quantum mechanics.”