AI Now Summit 2026
Mistral released an AI stack for industrial engineering at AI Now Summit 2026, partnering with Airbus, BMW and ASML to optimise design, simulation and production while retaining control over proprietary data and IP.
All AI news
All AI news
5 todayMay 28
Vibe gets to work.
Mistral upgraded Le Chat to Vibe, a unified AI agent covering work and coding, retaining all existing conversations, settings and subscription plans.
Introducing Search Toolkit
Mistral AI released the public preview of Search Toolkit, a composable framework for production search pipelines in AI applications. It unifies ingestion, retrieval and evaluation through shared interfaces, is open-source and deploys in cloud, local or edge environments.
Private analytics via zero-trust aggregation
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.
May 27
Introducing physics AI at Mistral: the foundation for engineering acceleration.
After incorporating Emmi AI, Mistral launched physical AI capabilities for AI-native industrial engineering with partners including ASML, Airbus, Safran and Siemens Energy. The model predicts physical fields directly from geometry and boundary conditions in seconds through one forward pass on a single GPU, versus hours to weeks per design variant in traditional CFD/FEM. It accelerates design iteration while retaining traditional solvers for validation and edge cases.
Physics AI research that’s shaping the industry.
Mistral acquired Emmi AI and doubled down on fundamental Physics AI research for aerospace, automotive, semiconductor and energy industries. Results include AB-UPT handling 9 million surface and 140 million volume elements on one GPU, and around 30,000 CFD simulations of transonic flow around 3D wings.
May 23
Emmi joins Mistral to accelerate the AI-native industry
Mistral AI signed a definitive agreement this week to acquire Physics AI pioneer Emmi AI, strengthening its AI transformation services for industrial companies. Founded in Austria, Emmi AI has over 30 researchers and engineers focusing on large engineering models that replace days of computation with real-time simulation and build digital twins. Its co-founders and team will join Mistral's Science and Applied AI teams in May.
May 22
Remote agents in Vibe. Powered by Mistral Medium 3.5.
Mistral released Mistral Medium 3.5, its first 128B dense model combining instruction following, reasoning and coding. Its weights are available under a modified MIT licence, with a 256k context window and self-hosting possible on a minimum of four GPUs.
Connect the dots: Build with built-in and custom MCPs in Studio
Mistral released Connectors in Studio. Built-in connectors and custom MCP are available through API/SDK for all model and agent calls, currently in public preview.
We’re launching the Google DeepMind Accelerator program in Asia Pacific to tackle environmental risks
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.
May 20
Empirical Research Assistance (ERA): From Nature publication to catalyzing Computational Discovery
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.
May 19
Fast-tracking genetic leads to reverse cellular aging
Google DeepMind's Co-Scientist accelerates cellular ageing reversal research, scanning tens of thousands of papers to propose over 20 testable new genetic factors. Several were validated in labs as driving cells towards younger states and improving overall function. It also cuts screening data analysis from six months to days.
May 18
Simulate real-world places with Project Genie and Street View
Google DeepMind added Street View grounding to experimental prototype Project Genie. Users select a real US location with a Maps pin, choose a style and describe a character, then Genie creates an interactive world whose starting location is grounded in real imagery.
Introducing Gemini Omni
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.
May 17
Gemini for Science: AI experiments and tools for a new era of discovery
Google DeepMind released Gemini for Science, launching three experimental tools on Google Labs: Hypothesis Generation based on Co-Scientist.
Making it easier to understand how content was created and edited
Google announced the expansion of content transparency and verification tools to Search, Gemini, Chrome, Pixel and Cloud. SynthID has watermarked over 100 billion images and videos and 60,000 years of audio. SynthID verification in the Gemini app has been used 50 million times and will reach Search and Chrome in the coming weeks.
May 16
Strengthening Singapore’s AI Future: A New National Partnership
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.
Finding the molecular switches behind new infectious diseases
Cambridge professor Clare Bryant uses Google Co-Scientist to study molecular mechanisms causing sepsis when pathogens such as influenza cross species. Generated and ranked hypotheses identified a previously overlooked protein and then specific amino acid sites. Her team is building cell lines carrying these mutations to test the hypotheses, expecting work that normally takes two to three years to finish in six months.
Opening new paths in aging research
Calico Life Sciences' Matt Onsum and Katherine Labbé use Google DeepMind Co-Scientist to integrate scattered ageing biology findings and generate testable hypotheses.
Accelerating discovery of liver disease mechanisms
A University of Edinburgh team used Google Co-Scientist to study MASH liver disease, integrating liver biology and pharmacology evidence to identify the NLRP3 inflammasome as a key molecular bridge between inflammation and metabolism. This explains why resmetirom works for only a minority of eligible patients. The experimentally validated hypothesis could advance targeted dual therapies.
Uniting biological toolkits for a new approach to ALS
Google DeepMind's Co-Scientist helps MIT mechanical engineer Ritu Raman rapidly review ALS literature, turn ideas into testable hypotheses and rank them by feasibility and risk-benefit balance.
Uncovering repurposed medicines to fight liver fibrosis
Gary Peltz's Stanford medical team used Google Co-Scientist to screen drugs. Two of three suggested candidates blocked fibrosis and promoted regeneration in living human liver cells, while both Peltz-selected drugs failed. Cancer drug vorinostat blocked 91% of damage responses driving scarring. The work appeared in Advanced Science.
How WeatherNext helped the National Hurricane Center better predict Hurricane Melissa’s historic landfall in Jamaica
WeatherNext, the AI weather model developed by Google DeepMind and Google Research, helped the US National Hurricane Center predict five days ahead with 80% confidence that Hurricane Melissa would make landfall in Jamaica at Category 5 strength. Confidence approached 100% three days ahead.
Gemini 3.5: frontier intelligence with action
Google DeepMind launched the Gemini 3.5 family with 3.5 Flash, focusing on agents and coding. It is available from today in the Gemini app, Google Search AI Mode, Google Antigravity, Gemini API and Gemini Enterprise.
May 12
Co-Scientist: A multi-agent AI partner to accelerate research
Google DeepMind published Co-Scientist research in Nature, describing a Gemini-based multi-agent AI system that iteratively generates, debates and evolves scientific hypotheses.
May 8
Adaptive Parallel Reasoning: The Next Paradigm in Efficient Inference Scaling
Berkeley AI Research reviews parallel reasoning, focusing on models deciding when to decompose and parallelise independent subtasks, how many threads to generate and how to coordinate. Existing approaches including Self-consistency, Best-of-N, Tree of Thoughts, MCTS, ParaThinker, GroupThink and Hogwild! Inference mostly impose parallel structures externally rather than teaching adaptive behaviour.
May 6
AlphaEvolve: How our Gemini-powered coding agent is scaling impact across fields
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.
May 2
Catalyzing scientific impact through global partnerships and open resources
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.
Apr 30
Enabling a new model for healthcare with AI co-clinician
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.
Four ways Google Research scientists have been using Empirical Research Assistance
Google Research described how scientists use Empirical Research Assistance (ERA) to advance research in four areas: epidemic forecasting, cosmology, carbon monitoring and neuroscience.
Apr 27
Workflows for work that runs the business
Mistral AI released Workflows in public preview, positioning it as an enterprise AI orchestration layer with durable execution, observability and fault tolerance to take AI workflows from proof of concept to production.
Announcing our partnership with the Republic of Korea
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.
Apr 23
It's all about the angle: Your photos, re-composed
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. The feature already applies automatically to photos containing people, with reframed versions available among Auto frame candidates.
Apr 22
Decoupled DiLoCo: A new frontier for resilient, distributed AI training
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.
ReasoningBank: Enabling agents to learn from experience
Google Research released the ICLR paper ReasoningBank, an open-source agent memory framework that distils high-level reasoning patterns from successful and failed experiences.
Apr 21
Partnering with industry leaders to accelerate AI transformation
Google DeepMind announced partnerships with Accenture, Bain & Company, BCG, Deloitte and McKinsey to scale frontier AI in enterprises. Partners get early access to models including Gemini and develop industry-specific solutions for finance, manufacturing, retail and media and entertainment. Currently only 25% of organisations have scaled AI into production.
Apr 20
Gradient-based Planning for World Models at Longer Horizons
Berkeley AI Research proposed GRASP, a gradient-based planner for learned world models. It lifts trajectories into virtual states for parallel optimisation across time, injects randomness directly into state iterations for exploration and reshapes gradients to give actions clear signals. Avoiding fragile state-input gradients in high-dimensional visual models makes long-horizon planning more practical and robust.
Apr 16
Designing synthetic datasets for the real world: Mechanism design and reasoning from first principles
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.
AI-generated synthetic neurons speed up brain mapping
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.
Gemini 3.1 Flash TTS: the next generation of expressive AI speech
Google DeepMind launched Gemini 3.1 Flash TTS, a new text-to-speech model emphasising stronger controllability, expressiveness and audio quality. From today, developers can preview it through Gemini API and Google AI Studio, enterprises through Vertex AI, and Workspace users can use it in Google Vids.