Things I wish I had learned at university: - measuring the efficiency of an algorithm in watts - difference between classical math and computation - relationship between geometry and number theory
That was very interesting. Do you have thoughts on actually cashing out the robustness gains via design of cheap+crappy chips that can be composed to deliver the performance/endurance of more expensive ones?
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I have daydreams, but mainly, if we can make the big step of shifting the hardware-software contract from determinism to best effort, then the chip folk will absolutely optimize cheap+crappy for us.
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Your ideas have put a number of thoughts in my mind. For instance, what is the smallest probabilistic compositional reward optimizer? What priors should it get for compositional self organization? Does it work better with centralized infrastructure that spawns an architecture?...
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the more I dig into this stuff the more I feel like it's what blockchain should actually be
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eg, instead of depending on mathematical proofs that can have security holes and only have guarantees when certain assumptions are met (51% power held by good actors), you have a system that can recover from attacks and can evolve for more uses
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To run arbitrarily close to the efficiency limit you have to run arbitrarily slowly. That’s a problem... Second problem is that you become ever more susceptible to thermal noise. In principle ECC fixes this — at ever growing complexity.
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Right! All scaling roads lead to best effort, if we are serious about making the journey.
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unsure about the performance possibilities but I think it's more focused on antifragility—in one example he shows introducing a virus and then a kind of white blood cell. the other benefit is that you can build really big systems that might be partially distributed
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