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Briefings and ideas about Research attribution from AI podcast discussions and the research they cite, with links to the original sources.
OpenAI posted hundreds of AI-produced math manuscripts on October 6 and withdrew three a day later. A mathematicians' group objected; on Moonshots, Alex Wissner-Gross argued math is just the first field AI will bulk-solve.
Eric Weinstein says AI should be free to challenge math and physics leaders he accuses of holding their fields back. He calls agent swarms on the internet dangerous. He believes a rigorously air-gapped, problem-solving AI would be safe to run, but he acknowledges that its research might give it new means of escape.
Goodfire's Eric Bigelow said its Silico agent did the research for his Forking Fast paper within a week. He says researchers still need to supply context, close guidance and the scientific taste that agents don't yet have.
After the 2026 medicine Nobel for optogenetics, Moonshots panelists argued the prizes lag AI-era science. Alexander Wissner-Gross said he once nudged Ed Boyden toward the field after reading Vernor Vinge.
A preprint credits an unreleased Claude model with the seed of a 3SUM algorithm just below quadratic time. On Moonshots, the result was cited in an argument that labs' internal models are pulling away from open ones.
OpenAI researcher Noam Brown says multi-agent coordination deserves not even 10% of the credit for the claimed Navier–Stokes result. He adds that OpenAI has not run a single-agent comparison or measured what 10,000 agents added.
Panelists split over whether OpenAI's Navier–Stokes proof means AI will soon improve AI research; a skeptic called math narrower, while a risk-focused guest gave about 10% odds a bigger agent swarm designs a better AI architecture in six months.
OpenAI says an internal model running about 10,000 agents for 88 hours produced a forced Navier–Stokes blowup construction with a Lean-checked proof. Moonshots panelists stressed it concerns idealized fluids and noted disputes over credit.