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Briefings and ideas about Superintelligence from AI podcast discussions and the research they cite, with links to the original sources.
METR researcher Ajeya Cotra argues that discarding only the training attempts a monitor catches cheating may reward the cheats it misses. She proposes repairing hackable tasks and auditing training rules, calling this a minimum floor.
Moonshots panelists debated a relayed claim that 70% of China's AI token use goes to video: Alex Wissner-Gross said US labs chase revenue per token, and Dave Blundin that video sells where enterprises won't trust Chinese models.
Konstantin Kisin told Steven Bartlett that Geoffrey Hinton's idea of a mother-like protective AI fails because maternal care rests on genes a machine lacks; a panelist warned such protection would amount to control.
Alvin Graylin argues China is competing to spread useful AI through industry and open-weight models adopted abroad, not racing to reach AGI first. The contrast is one of emphasis: America's AI Action Plan also promotes adoption.
Physicist Brian Greene argued with an AI on The Diary of a CEO that self-improving AI may approach a ceiling set by its architecture, not accelerate indefinitely—while warning that if no ceiling exists, gains could outpace human oversight.
Meta released Muse Glimmer, a 30-billion-parameter open-weight model built to run agents on suitably equipped PCs. Moonshots panelists debated whether it puts users in charge or strengthens Meta's hold through its existing apps.