At AISTATS 2026, Google Research proposed Regularized f-Divergence Kernel Tests for machine unlearning audits, using relative distances to determine whether models are closer to safely retrained versions or original compromised models.
Google DeepMind released experimental open-source model DiffusionGemma, generating text blocks in parallel through text diffusion and achieving up to 4 times faster inference on dedicated GPUs.
Google DeepMind and partners announce a $10M funding call for multi-agent safety research.
Gemini 3.5 Live Translate brings near real-time, natural speech translation to Google AI Studio, Google Translate and Google Meet.
Google DeepMind released Gemma 4 12B, a multimodal model for local laptop use between the edge-focused E4B and 26B MoE. Its unified encoder-free architecture feeds visual and audio inputs directly into the LLM backbone.
Google DeepMind launched a three-month Robotics accelerator for 15 early-stage European robotics start-ups, providing technical guidance and access to its AI stack and Gemini robotics models. Covering logistics, manufacturing, healthcare, climate and navigation, it starts in London this week.
Results from a randomized controlled trial show the potential of Gemini’s Guided Learning feature to boost engagement and accelerate learning.
When will markets price the singularity?
Google launched a public preview of Agentic RAG-powered cross-corpus retrieval on Gemini Enterprise Agent Platform. Roles including Orchestrator, Planner, Query Rewriter, Search Fanout and Sufficient Context Agent collaborate on multi-source, multi-hop queries.
Google Research published a study in Nature introducing PHRM, which records video with a phone’s front camera in the seconds after face unlock and uses deep learning to estimate heart rate and resting heart rate in the background.
Google Research open-sourced its hydrological modelling framework on GitHub under Apache 2.0, enabling national weather and hydrology agencies to integrate AI flood forecasting. The Python package uses PyTorch and an LSTM architecture, can train or fine-tune on Caravan data, and includes interactive tutorial notebooks and videos.
Google Research unveiled the experimental Gemini for Science toolkit at I/O 2026, including Computational Discovery based on ERA and AlphaEvolve, Hypothesis Generation based on Co-Scientist and Literature Insights based on NotebookLM.
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.
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.
Google released Empirical Research Assistance (ERA), a research tool using Gemini to write and optimise scientific code. Its paper was published in Nature today, and the tool is available to scientists worldwide as part of Gemini for Science.
Biologists use Co-Scientist to find novel factors that successfully rejuvenate human cells.
We’re expanding access to Google AI Ultra subscribers globally and introducing a new capability powered by Street View.
Google DeepMind released Gemini Omni Flash, the first model in the Gemini Omni family, generating high-quality video from combined image, audio, video and text inputs and supporting iterative video editing through natural-language conversations.
A collection of science tools and experiments to expand the scale and precision of scientific exploration.
We're expanding our tools to help you understand how content was created and edited across the web.
Google DeepMind and Singapore partner to apply frontier AI to address complex challenges across health, education, and sustainability and more.
Clare Bryant uses Co-Scientist to identify genetic triggers in emerging infectious diseases.
Calico Life Sciences uses Co-Scientist to connect scattered findings and generate new leads in aging research.
Filippo Menolascina uses Co-Scientist to identify new liver disease treatments and explain why existing drugs only help certain patients.
Co-Scientist unites Boston Children’s Hospital and MIT’s labs to explore new RNA-based treatments for ALS.
Stanford geneticist uses Co-Scientist to help find new treatments for chronic liver disease and liver fibrosis.
Learn how our WeatherNext AI model help forecasters give communities unprecedented time to prepare ahead of the historic Hurricane Melissa.
Gemini 3.5 is built to help you execute complex, agentic workflows.
Introducing Co-Scientist, a collaborative AI partner built with Gemini to help researchers accelerate scientific breakthroughs.
Explore how AlphaEvolve's Gemini-powered algorithms are driving impact across business, infrastructure, and science.
Google Research said its open-source tools and datasets have enabled over 250,000 researchers and developers worldwide. Genomics tools DeepVariant, DeepConsensus and DeepPolisher have supported processing exomes and whole genomes from 2.5 million people; MedGemma has over 4.8 million downloads. Open Health Stack is deployed in more than ten countries, reaching over 65 million beneficiaries.
Researching the path to AI-augmented care and development of an AI co-clinician.
Google Research described how scientists use Empirical Research Assistance (ERA) to advance research in four areas: epidemic forecasting, cosmology, carbon monitoring and neuroscience.
Google DeepMind and Korea partner to accelerate scientific breakthroughs using frontier AI models
Google Research introduced a new method in Google Photos’ Auto frame to change camera viewpoints after a photo is taken. An internal 3D point-map estimation model reconstructs the scene and focal length, then a generative latent diffusion model fills gaps exposed by the new view. It automatically detects faces and wide-angle distortion to suggest ideal framing.
Google DeepMind published a paper proposing Decoupled DiLoCo, splitting large-scale training into decoupled compute islands that communicate through asynchronous data streams, isolating local hardware failures.
Google Research released the ICLR paper ReasoningBank, an open-source agent memory framework that distils high-level reasoning patterns from successful and failed experiences.
Google DeepMind partners with global consultancies to bring the power of frontier AI to organizations around the world.
Google proposed Simula, a reasoning-first synthetic data framework reframing dataset construction as mechanism design. It builds datasets from scratch without seed data through global diversification, local diversification, complexification and dual-critic quality checks.
Google Research proposed MoGen (Neuronal Morphology Generation), using PointInfinity point-cloud flow matching to generate synthetic neuronal shapes and supplement PATHFINDER reconstruction training. It reduced reconstruction error by 4.4% on held-out mouse axons, mainly by reducing merge errors.