An AI publication
For readers who want to understand important AI developments and keep following the questions that matter.
Our articles start from AI podcast conversations and the research papers and articles they cite, with links to the original material.
A briefing reports one development at a point in time. We may correct or clarify it later; a new development gets a new briefing. How our formats work
In a preprint, Cameron Berg and Casper Kaiser report that steering a hidden good-or-bad signal in language models shifted their later choices between arbitrary zones while recall mostly held. The effect was robust in five of seven models tested.
On Moonshots, Peter Diamandis showed a speech implant from his portfolio company Paradromics and described Sabi's planned brain-reading cap. Dave Blundin argued that AI agents may reverse what such interfaces are for.
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.
Dave Blundin said today's AI forgets mistreatment like a goldfish once its context is flushed. On Moonshots, Alex Wissner-Gross countered that tools like Claude Code already save notes to files, so "I wouldn't count on it."
Alexander Wissner-Gross forecast that virtual-cell AI will propose small-molecule cures for the top 5,000 diseases within two to three years. He said regulatory approval would be a harder, policy-dependent question.
Computer scientist Alex Wissner-Gross argued that AI solving math at scale, not quantum computing, is the real threat to encryption, though he named no broken system. Salim Ismail countered that AI can also build stronger cryptography.
Meta released Muse Wonder, a model built to remember users over time, on October 12. On Moonshots, Alex Wissner-Gross said it trails the frontier once cost counts; Salim Ismail said knowing users best may decide the next big AI contest.
Anthropic's policy, effective November 12, bans sustained, purposeless cruelty to Claude but allows frustration and testing, citing uncertainty about Claude's moral status. Moonshots hosts debated whether AI training can cause suffering.
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.
Leash Bio co-founder Ian Quigley says messy DNA-encoded library screens can yield reproducible AI training data, using dozens of barcodes per molecule and hundreds of screens per library. He says absolute binding strength is still out of reach.
Ian Quigley says co-folding models still place a molecule where a pocket was digitally destroyed, so Leash Bio engineers protein mutants for negative data. In a 20-protein exploratory analysis, its model's attention spread more evenly after retraining on mutants plus about 40% more ordinary data.
In Leash Bio's 2024 Kaggle contest, no team beat chance on an unseen chemical library. Ian Quigley says Leash's later Hermes model roughly matched Boltz on public tests without training on outside data, but published results were mixed.
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