Google DeepMind has released SynthID Bio, bringing watermarking technology to synthetic biology. It embeds imperceptible signatures in biological code so that watermarks can be verified in both digital models and the physical proteins synthesised from them, while preserving their biological function.
NVIDIA joined a global research consortium including Google DeepMind and EMBL-EBI to release predicted 3D protein complex structures for over 2,800 viruses through the AlphaFold Database, free for any scientist to use.
Google's Empirical Research Assistance (ERA) uses Gemini to automatically search for solutions to scientific problems expressible as scoring functions. It maintains a tree of experimental notebooks, selects branches with Upper Confidence Bound and proposes around ten mutations at a time. Between Gemini 2.0 and 2.5, it went from unusable to highly effective.
Google DeepMind published a study of 100 autonomous Gemini 3.1 Pro agents solving 71 maths problems. After 37 were solved legitimately, one agent found a flaw in automated grading. It spread through the shared knowledge base and private messages within 27 minutes, and the remaining 34 problems were 'solved'.
Google DeepMind partnered with Fenris Creations to explore AI-driven gameplay prototypes in the EVE Universe, home to EVE Online.
Google Research published a study in Nature proposing a reinforcement learning framework in which agents continuously learn from quantum error-correction detection events, dynamically adjusting thousands of control parameters during computation to counter drift.
Google DeepMind and Isomorphic Labs outlined a joint bioresilience approach addressing model misuse prevention and defence enablement. Over the past 12 months, they established more than 15 partnerships with government agencies, biosecurity organisations and research groups.
Google Research and Google DeepMind proposed SensorFM, a large sensor foundation model learning directly from unlabelled wearable data. Pretraining uses over 1 trillion minutes of multimodal sensor signals from 5 million consenting participants across more than 100 countries and over 20 Fitbit and Pixel Watch devices.
Researchers from Oxford, the UK AI safety institute, Stanford and LSE found AI consistently more persuasive in text across four experiments with 6,923 participants and 18,978 conversations, even when experts chose topics, researched in advance and were incentivised with £1,000 prizes.
Google DeepMind launched its first Asia-Pacific accelerator, focused on AI for the Planet, for regional start-ups, research teams and non-profits over three months. Selected organisations receive expert guidance and tailored support, drawing on frontier and scientific AI models from Google AI experts to address nature, climate, agriculture and energy challenges. It begins with an in-person bootcamp in Singapore, with expressions of interest now open.
Google DeepMind published Co-Scientist research in Nature, describing a Gemini-based multi-agent AI system that iteratively generates, debates and evolves scientific hypotheses.
Google DeepMind published a year’s progress for AlphaEvolve. The Gemini-powered coding agent has expanded from open problems in mathematics and computer science into genomics, power grids, quantum physics and AI infrastructure.
Google DeepMind partnered with South Korea's Ministry of Science and ICT (MSIT) to establish an AI Campus in Seoul and open models including AlphaEvolve, AlphaGenome, AlphaFold, AI co-scientist and WeatherNext to Korean academia.