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 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.
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.
Mistral upgraded Le Chat to Vibe, a unified AI agent covering work and coding, retaining all existing conversations, settings and subscription plans.
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.
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.
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.
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.
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.
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.
Google DeepMind released Gemini for Science, launching three experimental tools on Google Labs: Hypothesis Generation based on Co-Scientist.
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.
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.
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.
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.
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.
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.
Mistral AI released Spaces CLI for human developers and coding agents. Commands such as spaces init and spaces dev handle scaffolding, development environments and deployment, with a corresponding flag for every interactive prompt so agents can work autonomously end to end. Each init generates context.json and AGENTS.md to provide structure and rules.
Google DeepMind unveiled an experimental Gemini-powered AI pointer that understands not only what it points at but what it means to the user. The team proposed four interaction principles: avoiding workflow interruption, capturing nearby visual and semantic context, supporting natural shorthand such as “this” and “that”, and turning pixels into actionable entities such as places, dates and objects.
Google released Vibe Coding XR, combining Gemini with the XR Blocks framework based on WebXR, three.js and LiteRT.js to turn natural language prompts directly into physically aware Android XR apps, reportedly in under 60 seconds.
Mistral AI launched Forge, a system for enterprises to build frontier-class AI models on proprietary knowledge, supporting pre-training, post-training and reinforcement learning. It handles dense and MoE architectures and, when needed, multimodal inputs, with training and governance on companies' own infrastructure.
Google introduced urban flash-flood forecasts on Flood Hub, using a new AI approach to predict risks in urban areas up to 24 hours ahead.
Google Research released WAXAL, a large open speech dataset initially covering 27 sub-Saharan African languages spoken by more than 100 million people, under CC-BY-4.0.
Mistral released the terminal coding agent Mistral Vibe 2.0, powered by the Devstral 2 model family, adding custom subagents, multiple-choice clarifications, slash-command skills, unified agent modes and automatic updates.
Mistral released Mistral AI Studio, a production AI platform for enterprise teams built on three pillars: Observability, Agent Runtime and AI Registry.
Le Chat Memories combines automatic saving, intelligent recall and visible sources. Users can disable memory, start memory-free incognito chats, edit or delete individual entries, export and import from other platforms. Memory Insights highlights trends and summaries from personal data, with categorisation and instant forgetting planned.
Mistral launched a beta directory of more than 20 secure MCP-based connectors in Le Chat across data, productivity, development, automation and business. It connects tools including Databricks, Snowflake, GitHub, Atlassian, Asana, Outlook, Box, Stripe and Zapier, and supports custom connectors or any remote MCP server.
Mistral AI released Codestral 25.08 and a complete enterprise coding stack comprising Codestral, Codestral Embed, Devstral and the Mistral Code IDE plugin.
Mistral added features to Le Chat including preview Deep Research, Voxtral-powered voice mode, multilingual reasoning with Magistral, Projects for organising conversations and image editing with Black Forest Labs.
Mistral AI launched Mistral Compute, a private integrated AI infrastructure stack covering GPUs, orchestration, APIs, products and services, ranging from bare-metal servers to fully managed PaaS.
Mistral released Mistral Code, an AI coding assistant combining Codestral, Codestral Embed, Devstral and Mistral Medium. It supports cloud, dedicated-capacity and local air-gapped GPU deployment, keeping code within enterprise boundaries.
Mistral AI released Agents API, combining its language models with built-in connectors for code execution, image generation, document libraries and web search, plus MCP tools, persistent memory across conversations and agent orchestration.
Mistral released enterprise AI assistant Le Chat Enterprise, powered by the new Mistral Medium 3. It offers enterprise search, agent building, custom data and tool connectors, document libraries, custom models and hybrid deployment, with all features rolling out over the next two weeks.
Mistral AI introduced Mistral OCR, an optical character recognition API that reads images and PDFs and outputs text and images interleaved in order. It is already the default document understanding model for millions of Le Chat users.