I haven’t justified either of those statements; I hope to make the complete arguments in upcoming posts. For now I’ll just say that human cognition is solving tough problems, and there’s no good reason to think that algorithms would be lots more efficient than networks in solving those problems.
I’ll also reference Morevec’s Paradox as an intuition pump. Things that are hard for humans, like chess and arithmetic are easy for computers (algorithms); things that are easy for humans, like vision and walking, are hard for algorithms.
I definitely do not think it’s pragmatically possible to fully interpret or reverse engineer neural networks. I think it’s possible to do it adequately to create aligned AGI, but that’s a much weaker criteria.
I haven’t justified either of those statements; I hope to make the complete arguments in upcoming posts. For now I’ll just say that human cognition is solving tough problems, and there’s no good reason to think that algorithms would be lots more efficient than networks in solving those problems.
I’ll also reference Morevec’s Paradox as an intuition pump. Things that are hard for humans, like chess and arithmetic are easy for computers (algorithms); things that are easy for humans, like vision and walking, are hard for algorithms.
I definitely do not think it’s pragmatically possible to fully interpret or reverse engineer neural networks. I think it’s possible to do it adequately to create aligned AGI, but that’s a much weaker criteria.
Please fix (or remove) the link.
Done, thanks!