OpenAI’s math breakthrough played to AI’s strengths

I tried to explain OpenAI’s solution more clearly than OpenAI did.

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[melgross]

It makes a lot of sense to me that even "non thinking" ML of whatever flavour could find a lot of previously unnoticed connections between the tree branches of knowledge - be this in Maths Chemistry or Biology; as the article notes finding these connections can take rare overlapping knowledge areas. Once you have the compute ability you can (if interested) just throw more compute at randomish directions until one of them returns something interesting.

Whilst genuinely new advances might come earlier in Maths, I think new advances in Chemistry, Biology and similar are going to be slower because of the lab requirements. Well, if and until those go dark too - and at that point we're possibly getting into weird "magic" technology.

Several years ago Google’s A.I. solved a major problem in biology with the problem of generalized protein folding. That was something that had been seemingly impossible to solve. I’m certain that we will see more of that happening.

 

[melgross]

When we talk about current A.I. as not really A.I., but versions of statistical modeling, I agree. These models seem to be limited in actual abilities to actually “think”. But for these who believe that this is the best we can do, and therefore we will just see ever shrinking growth in capabilities, I believe that’s likely wrong.

The current work isn’t necessarily the only way A.I. can be implemented. Researchers are working on other models that may provide better capabilities and work more closely to what we believe is actual thinking and reasoning.

That said, there is no reason to believe that the way humans (or animals) think is the only, or even the best way to accomplish it. We may be way down in the scale of brain organization and efficiency. It’s just the way it evolved here. Birds have a fairly different way of organizing neurons. Who knows, perhaps that’s even better than ours.