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Google DeepMind used a large language model to solve an unsolvable math problem
(www.technologyreview.com)
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this post was submitted on 15 Dec 2023
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So, they basically "intelligently" brute forced it? Still cool.
Isn't that how we learn too? We stop doing the things that don't work in favor of things that do while repeatedly "brute forcing" ourselves (training/practice).
It's more like educated guessing, which is a lot faster than brute forcing. They can use code to check the answers so there is ground truth to verify against. A few days of compute time for an answer to a previously unsolved math problem sounds a lot better than brute forcing.
Generate enough data for good guesses and bad guesses and you can train the thing to make better guesses.
it is what we (the people) do as well. we look at the data and try to find a pattern. but the computer can process larger amount of data than people can.that's it.
no. your claim sounds ridiculous.
I didn't claim anything. I asked. If I'm misguided, then so be it, I'll learn somthin'.
Well don't be a poopy pants!
It's not brute forcing though. It is similar to genetic programming, it seems, but with more less understood parts.
I mean, I would also call genetic algorithms a form of brute forcing. And just like with genetic algorithms, this approach is going to be severely limited by the range of values that can be updated and the ability to test the outcome.
Why would you not be able to test the outcome fully? And what do you mean by "limited by the range of values that can be updated"?
So they configured the experiment so that only certain lines of code were able to be iterared/updated. Maybe you could ask it to start from scratch, but I imagine that would increase the time for it to converge (if it ever does).
Regarding testing, not all mathematical proofs can be verified by example. Here they were trying to prove that there was an even lower bound for the problem, but not all proofs will work with that structure.