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SoylentRox t1_iu0qt8k wrote

Yeah basically. Typing on my phone but yes. Basically like if you want to engineer a gear train you are really asking for "the cheapest set of gears that does function X, has a 99 percent chance of working past warranty period Y, and fits in as small as space as possible".

So the machine can propose various gear sets and you can auto score how well it met the 3 terms I gave above.

It can use that score as an RL signal to propose better gears.

At scale - with millions of simulated years of practice and hundreds of thousands of variations of the "design a gear train" problem - even a very stupid algorithm that learns poorly will still be better than any human alive.

Simply by brute force - it has more experience and can propose a thousand solutions in the time a human engineer needs to propose one.

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