Models that plan, call tools and finish multi-step tasks on their own: from Claude Code and Manus to agent frameworks and benchmarks.
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.
We’re expanding access to Google AI Ultra subscribers globally and introducing a new capability powered by Street View.
A collection of science tools and experiments to expand the scale and precision of scientific exploration.
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.
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.
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 released the ICLR paper ReasoningBank, an open-source agent memory framework that distils high-level reasoning patterns from successful and failed experiences.
Google DeepMind is transforming the mouse pointer into a context-aware AI partner. Move beyond the friction of traditional prompting with intuitive AI collaboration in Chrome and beyond.
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.
Today, we’re introducing Forge, a system for enterprises to build frontier-grade AI models grounded in their proprietary knowledge.
Mistral built an autonomous agent on its open-source coding assistant Vibe to read Rails source files, generate or improve RSpec tests and run within CI/CD without human intervention.
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 AI released the next-generation Devstral 2 coding family, including 123B Devstral 2 under a modified MIT licence and 24B Devstral Small 2 under Apache 2.0, both open-source.
Mistral has released Mistral AI Studio, a production-grade AI platform for enterprise teams built on three pillars: observability, Agent Runtime and AI Registry.
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.