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
Leash Bio co-founder Ian Quigley says a model given only guesses of who made each molecule, plus the target protein's identity, predicted public ChEMBL activity data nearly as well as one using structure plus the same protein. His team's preprint adds that those guesses still carry chemistry.
Ian Quigley of Leash Bio says AI agents querying its premeasured binding screens can search for strong binders within 100 picks, and argues this resists memorization better than scaling its Hermes model. Leash released a version, Minos, October 14.
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.
GovAI's Alan Chan argues that AI labs should commit to pausing on specific warning signs, such as an agent escaping its sandbox, with embedded auditors checking. He prefers this to a set cap on AI progress and is still drafting the triggers.
GovAI researcher Alan Chan said there is basically no system telling websites that an agent is acting or who runs it. He would start by naming the inference provider, and he now gives less priority to open-web authorization rules than to monitoring and security inside companies and to identification that supports incident investigation.
GovAI's Alan Chan expects rogue AI agents to persist online and outlines how they could earn, steal and cause harm. He puts takeover odds at 1% to 10% over five to ten years, while saying his forecasts are poorly calibrated.
GovAI's Alan Chan says real-time agent monitors should have been standard sooner, and suspects risks may concentrate in labs' testing and training rather than products. Tamper-evident logs, he says, are a matter of will.
Jason Ma, Dyna Robotics' co-founder and chief scientist, says the company must own its robot hardware because of latency, human-data transfer and long supply chains. He also says wheels beat legs for now.
Dyna Robotics chief scientist Jason Ma argues that robots should predict future camera video, not only their next moves. He says the bet could fail if touch or sound makes rival models far more data-efficient.
Jason Ma, chief scientist at Dyna Robotics, says robotics has no internet of data. Dyna pretrains on a million hours of human video, adapts each task with minutes to hours of robot data, and Ma expects synthetic environments to add more.
Jason Ma, chief scientist of Dyna Robotics, says robots fold thousands of napkins daily across many Din Tai Fung locations in the US. He contrasts that with one-site pilots and says Dyna aims for hundreds of robots next year.
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