Google DeepMind, Schmidt Sciences, Cooperative AI Foundation and ARIA, supported by Google.org, launched up to $10 million in global technical research funding focused on collective behaviour and safety risks in large-scale multi-agent AI systems.
Import AI covers three studies. King's College London, Fudan and Alan Turing Institute built SocioHack with 72 sandbox social environments to test RL exploiting institutional loopholes while complying with rules. Models rediscovered patched historical vulnerabilities with 61.25% recall and 90.85% precision.
Import AI 459 focuses on three studies: a UK AI Safety Institute paper says automated alignment research using AI to supervise AI training is not a universal solution and is harder to implement than expected; other work covers scaling laws for protein-folding models and pricing AI-system extinction risks.
Google combined a new single-message encrypted aggregation protocol with TEEs, letting devices submit without multiple online rounds. Google receives only anonymised group insights; raw data is neither exposed nor reconstructed even within hardware protection. TEE attestation proves execution follows public code.
Import AI 457 focuses on three studies. SentinelOne analysed fast16.sys, malware from over 20 years ago that sabotages engineering and physics simulations by altering in-memory results from precision software such as LS-DYNA 970, PKPM and MOHID.
Google DeepMind and Singapore's government formed a national AI partnership with new projects in healthcare, research, education and climate. It explores an AI-assisted triadic-care model, uses AlphaFold and Google Earth for Southeast Asian infectious-disease research and develops a Gemma-based running assistant to help visually impaired athletes train independently.
The Institute for Law & AI proposed radical optionality in regulation: governments should avoid excessive regulation now while building information gathering, whistleblower protection, evaluation and model-weight security capabilities to respond quickly when powerful AI affects the world. A Meta and KAIST paper proposed a Neural Computer unifying computation, memory and I/O in learned runtime states.
Google DeepMind announced AI co-clinician research to explore AI agents assisting patient care under clinical supervision. In blinded assessments of 98 real primary-care queries, 97 responses had no critical errors, and doctors preferred them to existing evidence-synthesis tools. Across 140 consultation skills, AI matched or exceeded primary-care doctors on 68, but expert doctors were better overall at recognising red flags and guiding key physical examinations.
Google Research proposed situational judgement tests (SJT) adapted from psychological questionnaires such as IRI and ERQ to evaluate alignment between LLM behaviours and human consensus in real user–assistant scenarios.
Google Quantum AI published a white paper saying future quantum computers would require fewer qubits and gates than previously estimated to break the elliptic-curve cryptography protecting cryptocurrencies.