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Reporting and discussion about Models & Research, with links to the original sources.
Gamow Labs founder Daniel McKinnon says startups like his can't compete on building models. His team combines frontier models, builds tools and tests the whole system, and he says that layer is thinning as models improve.
At DevDay, OpenAI API product lead Nikunj Handa said GPT-6 lets agents keep reasoning while tools run and take new instructions mid-task. He also described longer cache guarantees, one still in preview, and open questions about the platform.
OpenAI's Nikunj Handa says the Decisions API, inspired by TypeSafe's Jev, began about a week before DevDay and runs on existing Luna weights, not a new model. He agreed confidence calibration may need future model work.
Alexander Wissner-Gross argued AI models are a weak form of mind uploading. The closest matching study, from 2022, found GPT-2 partly predicted 101 listeners' brain scans, but only correlationally, reaching at most 32% of the noise ceiling.
Alexander Wissner-Gross told a founder whose AI language companion kept slipping into assistant mode to try fine-tuning; Dave Blundin suggested an open-weight GLM model and said learners want to be fluent and funny, not just correct.
Robinhood CEO Vlad Tenev argued AI research is easier to automate than consumer apps because its experiments have ready-made evals, while app changes must wait for enough users to show statistically significant gains.
OpenAI researcher Noam Brown says AI could make AI research perhaps three times faster. He argues that, unlike maths, research waits on sequential experiments and GPUs, so he doubts a 100-fold jump, and says his uncertainty is large.
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.
Box CEO Aaron Levie says shifting access permissions, like a lawyer walled off from rival matters, complicate training company knowledge into model weights. He wants a rubric on what to bake in and expects answers to vary by domain.
Alexander Wissner-Gross argued next-word prediction as a training task may last indefinitely, while the transformer architecture is already being replaced piece by piece. Another panelist guessed chips move to photonics in 18 months to two years.
On the Dwarkesh Podcast, AI researchers argued that pass/fail rewards work because earlier training supplies candidate behaviors and rewards ignore incidental wording. Charlie O'Neill warned that harder training tasks cost ever more to build.