I think the later is misguided. So what if the AI labs are misaligned to math? - But they announced a result before a paper was peer reviewed! The horror! So what? The mathematics community can read the paper once it is written up. - But their results they publish may not care about conceptual understanding and insight! So what? If that's the mathematics community's goal, then they should sift through the lean proof and reformat the ideas to make them more insightful and develop their own conceptual understanding. - But they aren't bothering to do literature review to tell the history about how humans contributed to the final result! So what? If it's so important to the mathematical community, they can do that themselves and throw a party every Tuesday in the honor of Luis Martínez-Zoroa and wear jeans on casual Friday in honor of Buckmaster and Alpöge - the left leg for Buckmaster and the right for Alpöge. An AI giving a definite result of an open problem doesn't decrease the mathematical community's insight or conceptual understanding. They are still free to continue doing their work and pursuing their goals. If it's really so bad, they can just pretend they don't know NS is solved and keep spending their efforts trying to prove it never blows up (or a hand full of them can try to blow it up from scratch). Guess what! I spend no part of my life working on unsolved math problems. I read some books for pleasure. I work in a hospitable with sick kids. I help my wife raise our kids. My goals are misaligned with the mathematics community! I've done nothing to increase conceptual understanding and insight! So what?
* Frontier models need infinite high quality private IP to keep them fed. Forcing an IP theft funnel ensures big lab survival and model intelligence growth. * Open-weight models are 1month behind frontier models. Cheaper, faster, private (no IP theft), steerable (you can security harden your own software without safeguard triggers). No sane business would keep using these API services if they didn't have to. The labs stand to lose a fortune. * Dario has stacked the deck at METR, who are funded by all the same NGOs who are funded by Anthropic and its investors. METR is full of ex-Anthropic employees with massive equity stakes. If they manage to position METR as the "independent evaluator" for the industry, they control what gets evaluated, how, and who passes. * Creating a gap between what the public knows exists (model capabilities) and what is used in secret allows it to be weaponized against other nations and the public. * No requirement for public disclosure on model capabilities allows them to feign they've hit intelligence ceilings while they secretly RSI to the moon with better and better chips. * Slowly but surely, this will allow the big labs to swallow the entire economy and every single business on Earth, by cloning and automating. This, and many more reasons. The healthiest outcome we can hope for is if the labs feel more pressure to be held accountable for the incidents they cause (HF incident, etc), so they have an incentive to ensure it does not happen again. In general, accountability of what your AI models do is the solution, it creates the right incentives. That's all we need here - balanced incentives. Everything else should be left alone so the free market can naturally evolve to the best outcome where we're not enslaved by tech giants yet again.
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