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Google DeepMind and A24 have announced their first research-focused partnership, a long-term collaboration across several projects that will involve A24 and its filmmakers in shaping new technology. Google has also invested in A24. Initial work will focus on bridging frontier technology and next-generation entertainment, with specific goals and technical outputs to evolve over time.
Berkeley Artificial Intelligence Research (BAIR) has announced its 2026 PhD graduates, whose work spans robotics, LLMs and reasoning, computer vision, generative modeling, AI safety, human–computer interaction, and AI for science. Destinations include OpenAI, Mistral AI, Physical Intelligence, Amazon, and academic roles at UCLA and Princeton's CITP; some graduates are starting their own companies.
Google DeepMind is working with the UK government, Google Cloud, Faculty, and local planning departments in Barnet, Dorset, and Camden to develop an AI planning prototype based on Gemini. The goal is to cut decision times for residential planning applications by 50%.
Google DeepMind has published an AI Control Roadmap that treats internal AI agents as potentially misaligned and adds system-level safety layers beyond model alignment. It proposes grading safeguards by detection capabilities D1–D4 and prevention-and-response capabilities R1–R3.
Why it matters: DeepMind has published its internal AI control roadmap, with graded detection and response capabilities and analysis of one million coding-agent trajectories.
The alignment team at the UK's AI Security Institute and Timaeus have jointly founded Sequent, a nonprofit research organization. It argues that “alignment is not on track” and plans to grow to 40–80 full-time staff within two years, with an initial fundraising target of $100–150 million. Research areas include scalable oversight, learning theory, heuristic argumentation, game theory, and personas.
With Google's support, UC San Diego is using motherboards from 2,000 retired Pixel phones to build a data center offering low-cost, low-carbon cloud computing for hundreds of students and faculty. SPEC benchmarks show that 25–50 phones roughly equal one modern server; the phones are organized into self-managing Kubernetes clusters of 25–50 devices. The system is expected to launch in fall 2026.
Google DeepMind, Schmidt Sciences, the Cooperative AI Foundation, and ARIA, with support from Google.org, have launched a global call for technical research proposals on multi-agent AI safety, with up to $10 million in funding.
Google DeepMind has launched a three-month robotics accelerator, selecting 15 early-stage startups from across Europe and providing technical guidance and access to its AI stack and Gemini robotics models. The companies work in logistics, manufacturing, healthcare, climate, navigation, and other areas; they include Norway's 3D-Components, France's Bubble Robotics, and the UK's Touchlab. The program began in London this week.
At I/O 2026, Google Research introduced the Gemini for Science experimental toolkit, including Computational Discovery built on ERA and AlphaEvolve, Hypothesis Generation based on Co-Scientist, and Literature Insights based on NotebookLM.
After acquiring Emmi AI, Mistral is building foundational physical AI for aerospace, automotive, semiconductors, and energy. Its announced results include AB-UPT, which processes raw geometry with 9M surfaces and 140M volume cells on a single GPU without remeshing, and NeuralDEM, an end-to-end deep-learning surrogate for large multiphysics processes.
Mistral AI has signed a definitive agreement to acquire Emmi AI, a physics-AI company, to strengthen AI-transformation services for industrial enterprises. Headquartered in Austria, Emmi AI specializes in physical AI and large engineering models that can replace multi-day computations with real-time simulations and build digital twins. Its co-founders and more than 30 researchers and engineers will join Mistral's Science and Applied AI teams in May.
Google DeepMind has launched its first Asia-Pacific accelerator, focused on “AI for the Planet,” for startups, research teams, and nonprofits in the region. The three-month program provides expert guidance and help from Google AI specialists to integrate frontier and AI-for-science models into projects and products in nature, climate, agriculture, energy, and other fields. It begins with an in-person boot camp in Singapore; expressions of interest are now open.
Lilian Weng says she would love to see more collaboration and research in human-AI interactivity and points readers to @thinkymachines’ grants of $100,000 + Tinker credits for researchers in the field. Proposals are due June 19th. https://thinkingmachines.ai/news/interactivity-research-grants/
Google has announced that it is extending content transparency and verification tools across Search, Gemini, Chrome, Pixel, and Cloud. The Gemini app already supports SynthID verification for images, video, and audio, with 50 million uses to date. The feature is coming to Search today and Chrome in the coming weeks.
Why it matters: The source details where SynthID and C2PA verification are available across Search, Gemini, and Chrome, helping readers assess the practical reach of provenance tools.
Google DeepMind and the Singapore government have announced a national AI partnership with new projects in healthcare, research, education, and climate. The work explores a “triple-care” model for AI-assisted clinical care and uses tools including AlphaFold and Google Earth to advance infectious-disease research and epidemic preparedness in Southeast Asia. Gemini for Education will be available to educators from primary through junior college, and an Asia-Pacific “AI for the Planet” accelerator is also launching.
Some personal news: I am starting a new research project at Anthropic. Very excited about this! Many things are needed to make AGI go well, and alignment is only one of them. More on this soon…
Fixed (thanks, @vthallam) — any other feedback on voice and/or transcriptions? @vthallam says the fix is in for transcripts disappearing when a call comes in during ChatGPT dictation, and that it should roll out in one of the upcoming weekly releases. Turley says it’s fixed and asks for more feedback.
Google Research says its open-source tools and datasets have enabled more than 250,000 researchers and developers worldwide across fields including genomics, neuroscience, and Earth modeling. Tools such as DeepVariant have supported analysis of whole-genome and exome data from 2.5 million people, while the HAI-DEF model suite, including MedGemma, has been downloaded more than 4.8 million times.
Google DeepMind and South Korea's Ministry of Science and ICT (MSIT) have announced a partnership that will establish an AI Campus at Google DeepMind's Seoul office and give South Korean academia access to frontier models including AlphaEvolve, AlphaGenome, AlphaFold, AI co-scientist, and WeatherNext.
Google DeepMind has announced partnerships with Accenture, Bain & Company, BCG, Deloitte, and McKinsey to scale frontier-AI deployment in businesses. Partners will receive early access to frontier models including Gemini and direct access to Google DeepMind's technical teams, with work focused on agentic transformation in finance, manufacturing, retail, media, entertainment, and other sectors. Only 25% of organizations have successfully scaled AI into production so far.
At The Check Up, Google Research announced several healthcare-AI developments. Research with Fitbit found that the Personal Health Agent (PHA), which simulates a collaborative care team, better supports long-term health management than single-purpose applications.
Mistral AI joined the NVIDIA Nemotron Coalition as a founding member and plans to co-develop frontier open-source AI models with NVIDIA. Mistral will contribute model architectures, training techniques, multimodal capabilities, and fine-tuning tools, alongside NVIDIA’s compute and development resources. The coalition’s first initiative is a base model trained on NVIDIA DGX Cloud that will underpin the upcoming NVIDIA Nemotron 4 family and be open-sourced for post-training and specialization.
Why it matters: The coalition’s planned shared base model would give developers a common starting point for post-training and specialization, connecting the partnership to a concrete model-development workflow.
Mistral AI announced strategic commitments in Germany, including a multiyear partnership with SAP to deliver a fully sovereign AI stack for Germany and Europe, integrate its models into SAP’s AI Foundation, and co-develop industry-specific solutions. With Helsing, it is accelerating vision-language-action model development for defense and security applications. Mistral AI also plans to significantly expand its local team and open an office in Germany in the coming months.
Mistral AI announced a 1.7B€ Series C funding round at an 11.7B€ post-money valuation, led by ASML with participation from existing investors. The funding will support scientific research and custom decentralized frontier AI solutions for engineering and industrial problems. ASML said the strategic partnership aims to benefit its customers through AI-enabled products and solutions, with potential for joint research.
Mistral AI, Carbone 4, and the French Agency for Ecological Transition (ADEME) completed the first full lifecycle analysis of an AI model and disclosed the environmental footprint of Mistral Large 2: by January 2025, after 18 months of use, it had produced 20.4 ktCO₂e, consumed 281,000 m³ of water, and used 660 kg Sb eq.
Mistral AI has launched AI for Citizens, a collaboration program helping governments and public institutions use AI strategically to transform public services, drive innovation, and maintain competitiveness. The program is active in France, Luxembourg, Singapore, the Netherlands, the UK, Switzerland, and other countries. Options include self-hosted deployment, data sovereignty, customized R&D, and joint model training as alternatives to the closed, one-size-fits-all AI offerings that dominate the market.
Mistral AI has launched Mistral Compute, an integrated private stack spanning bare-metal servers to fully managed PaaS, including GPUs, orchestration, APIs, and products. As an NVIDIA partner, it will offer the latest NVIDIA reference architectures, with tens of thousands of GPUs available initially and rapid expansion planned over the coming years.
Why it matters: Mistral is productizing its in-house training and inference infrastructure, offering another option for sovereign AI compute in Europe.
