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> requiring 2^38 steps to find a solution Isn't the premise of the company to use "AI" to find a solution? I'm going to go out on a limb and assume AI here mea
by alephnan 9y ago
> requiring 2^38 steps to find a solution
Isn't the premise of the company to use "AI" to find a solution? I'm going to go out on a limb and assume AI here means deep learning. I took both an AI and ML course during college where the FAQ was "what's the difference?". At least from the way the courses were presented, the AI class focused on traversing these exponential search spaces. ML on the other hand searched for local maxima / approximations. Obviously, you seem more familiar with combinatorial auctions. I'd love to understand where an ML approach fits in here.
- sgt101 9y agoThe thing is that if your deepnet makes a mistake and classifies a penguin as a panda it's just one of those things. If it clears an auction outside of the guarantees that you have given then everyone sues you. The reasoners that people build for auctions and poker and so on are constructed to have well understood properties so that they can be used in applications like stocks and shares, organ transplants and other critical systems.
- sebastos 9y agoBased on the responses I'm seeing from user lpage elsewhere in the thread, it sounds like you can establish lower bounds external to the AI aspect of the settlement layer, making it "at least as good". So perhaps the optimization is, in some sense, all upside?