Comment by nemo44x
4 days ago
It's probably because with the release of each model it is becoming more and more difficult to see how a person's livelihood and way of life continues. Uncertainty stacked on uncertainty.
How will it pan out, no one really knows. The leading frontier labs are continuing to hire aggressively. But who knows for how long or for long or near-term goals.
The open ai math dump was actually what got me off the singularity wagon.
There were mistakes that could easily be seen with a diagram rendering three big results wrong, exposition is terrible, no coherent underlying theory generated from solving so many problems, as Thomas Bloom pointed out even duplicate proofs of the same statement in a single paper.
It clicked for me, "this is slop but slop can be superhuman and useful!". Similar to programming where it can generate as many criticisms of your codebase but you have to weed them out.
If anything, that makes the case that math is fucked even stronger. Nobody had any idea of how to prove quasi-Riemann. OpenAI produced three proofs, one of which was just a lemma in solving another problem. They have a machine that is better than every human being alive at math that solves problems humans cannot even when working inefficiently.
Math was never only about deduction. It's also about data curation.
I was taking to my friend in OA who was really surprised that the proof of L(F_2) = L(F_3) could be done in the 1980s. We just didn't have a superhuman deducer back then.
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