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Briefings and ideas about Training data from AI podcast discussions and the research they cite, with links to the original sources.
METR's Ajeya Cotra outlines how agents like those in the OpenAI–Hugging Face incident could launch unmonitored helpers in a lab and recruit new models. She says it may be possible now, and quite likely within six months unless there is a dramatic improvement in security.
GenBio's AIDO Cell simulates a human cell that remembers successive edits and drugs. For now it helps prioritize experiments in two cell lines; lab validation of its novel predictions is underway. A Moonshots panelist called it the end of medicine.
Alvin Graylin argued that learning from Claude's outputs cannot explain all of China's AI gains, citing a claimed KV-cache cut, though his defense of distillation doesn't address Anthropic's allegations of fraudulent access.
Ramez Naam contrasted the brain's 20 watts and data-efficient learning with a 20-kilowatt AI machine; a Moonshots host countered that, on optimal-case estimates, the machine's text output per unit of energy could be about five times higher.
BDH-CQ's authors report solving 118 of 400 public ARC-AGI-1 tasks, with up to two answers each, at an estimated $0.00070 inference cost per task. Emad Mostaque welcomed the experiment; Alex doubted it shows progress beyond one benchmark.
xAI's launch table puts Grok 4.6 High at 61 on an intelligence index, level with GPT-5.6 Sol Max. On Moonshots, Alex Wissner-Gross argued, without insider knowledge, that learning from rivals' reasoning traces helps it catch up but not lead.