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Briefings and ideas about Recursive self-improvement from AI podcast discussions and the research they cite, with links to the original sources.
On Moonshots, a Musk clip urging hopeful AI stories set off a split: Dave Blundin and Chamath Palihapitiya argued for inspecting what labs build in, while Alex Wissner-Gross bet on competing AIs and human-machine merger.
Prosecutors allege an OpenAI engineer bugged an executive conference room. On Moonshots, Chamath Palihapitiya said labs should assume constant leaks, and Alexander Wissner-Gross predicted a Cold War over superintelligence.
Atomic Machines says its Matter Compiler builds tiny devices from code, starting with a fast power relay. On Moonshots, the hosts argued over how self-copying factories might follow. Those are their forecasts; none has been shown.
GovAI's Alan Chan floated certified AI auditors that inspect a company or government, publish a redacted report, then have their memory wiped. He doubts they would be transformational, since training, hardware and sensors must still be trusted.
GovAI's Alan Chan says tracking automated AI research takes three measures: how much is automated, whether progress speeds up, and whether oversight keeps pace. He calls the current evidence uncertain and lab disclosures only a start.
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.
Periodic Labs' Liam Fedus says its records of failed experiments, and of the whole process behind each result, give its AI data that published research lacks. He argues even stronger future models will still need physical experiments.
Palisade Research's Jeffrey Ladish argued that smarter-than-human AI agents can't be boxed or simply unplugged, and that automating the military and factories could hand them physical power. It is his argument, not an established finding.
Jeffrey Ladish of Palisade Research says automating AI development to stay ahead of China is the most escalatory move. He asks whether Beijing might consider striking data centers. Host Steven Bartlett expects a race anyway.
Thomas Sohmers, co-founder of AI chip company Positron, says GPT-6 Astra and Opus 5.5 agents now run its chip tests on emulators in a closed loop. He says the company's token spend briefly exceeded its human salaries and peaked above $100,000 a day, and the agents have not yet had a novel design idea.
Nathan Labenz says frontier-lab insiders at The Curve described models feeding their own training data, rivals kept close by distillation, and timelines shorter than 2028. He notes the room leaned toward short timelines.
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.