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Terence Tao said the same[1]

> In fact, it is now the identification of a promising problem which is the scarce and precious resource. We have now seen that even the rumor of someone working on a problem can trigger a massive amount of AI-powered effort to flatten it before the original research project has time to reach its full potential. The incentives may now be pointing in the direction of no longer sharing any promising research directions with the broader community, which would reverse centuries of traditions of open science and do serious long-term damage to the future of the field.

[1] https://mathstodon.xyz/@tao/117237322160500501

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This reminds of Magnus Carlsen saying that if he were to cheat, all he would need would be a signal to spend more time on the current move.

> it is now the identification of a promising problem which is the scarce and precious resource

This is by no means new. Perhaps it is even more extreme now. Literally my first 1:1 with my PhD adviser back then, he told me that the most important thing about a researcher is the quality of the problems he picks.


Sure; if you define the quality of a problem by reference to your ability to solve it.

In the real world the quality of these esoteric problems is typically gauged by the difficulty of solving them.


> In the real world the quality of these esoteric problems is typically gauged by the difficulty of solving them.

I don't believe that's strictly true. Way oversimplified projection on one axis.


Could you just start engineering "leaks" of new proofs so that Anthropic or OpenAI just start burning $10million in compute

Shouldn’t this very capable model they’ve developed be able to identify promising problems? That’s what I’d expect from how the model is being presented and advertised.

That's more or less what they did according to their announcement. They fired it at a whole bunch of high end math problems and merely concentrated all efforts on one after it made some promising progress.

It seems like that’s the opposite of what happened. They started attacking the problem when they got a wind of a possible solution from certain individuals.

But they didn't know which problem had a possible solution. So they fired it at a huge amount of problems and then merely focused on the one that turned out to be promising. The model found the promising path itself, they just re-allocated the available resources once it became apparent.

i've seen no sign of that



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