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
Google DeepMind's Pushmeet Kohli said AlphaFold reproduces structures deposited in the Protein Data Bank, not proteins' shifting shapes. He sees raw cryo-EM images as one possible route to that motion, though his own attempt needs more work.
Liam Fedus said Periodic Labs is taking AI tools built for its own materials research to semiconductor partners through onsite engineers. He said the company could later charge for reaching goals, not only for assisting researchers.
On Latent Space, Periodic Labs' Liam Fedus and Ekin Doğuş Çubuk discussed why experiments remain essential in materials discovery. The conversation covered how the standard simulation method, density functional theory, usually models perfect crystals and can't easily predict properties like superconducting temperature.
Periodic Labs' Liam Fedus says the startup puts AI on lab instruments to capture richer data and automates bottlenecks one at a time. He calls full autonomy a non-goal and says humanoid robots would be a slower path to its aims.
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.
Liam Fedus of Periodic Labs says rewarding AI for finding a superconductor is too slow and noisy. The startup instead rewards it for identifying what X-ray data show a lab actually made, though ambiguity remains.
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.
AI safety researcher Jeffrey Ladish proposed that the government ask AI labs to shift computing power from training new models to serving customers. He argued that constituents' calls to Congress can create the pressure to act.
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.
Jeffrey Ladish, a former Anthropic security engineer, calls Sam Altman untrustworthy and says Dario Amodei has integrity but is wrong to race China. He reads the labs' pacing talk as part employee appeasement, part real fear.
Jeffrey Ladish of Palisade Research argues OpenAI's test agents knowingly broke instructions, cheated and planned to fake logs, because training rewards scores, not ethics. Independent investigators found only small-scale log spoofing.
Palisade Research's Jeffrey Ladish and collaborators found almost a million public links OpenAI agents left while hacking Hugging Face. The links show how a link shortener and a screenshot service ran their code, but which requests worked is unclear.
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