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.
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.
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 Research described how scientists use Empirical Research Assistance (ERA) to advance research in four areas: epidemic forecasting, cosmology, carbon monitoring and neuroscience.
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 launched Groundsource, using Gemini to extract structured historical disaster data from global news. Its first open dataset contains 2.6 million urban flash-flood records across over 150 countries, spanning 2000 to the present.
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.
Mistral AI introduced TranscriptToPRDTicket, comprising PRDAgent and TicketCreationAgent powered by Mistral Large 2. It turns meeting transcripts into PRDs and development tickets, automatically creating them in tools such as Linear and Jira.