The reading room
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.
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.
Alan Chan of GovAI proposes that AI systems be able to report misconduct they find. He would measure the tendency and give models an out, but not mandate it. A swarm study shows whistleblowers can appear yet fail without a monitored channel.
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.
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