Can autonomous AI advance the frontiers of scientific discovery? Join Rui Meng at the @COLM_conf Google booth (#107) today at 2:00 PM PT for a live demo of ScientistTwo, an autonomous multi-agent framework that analyzes research papers, identifies limitations, and produces verified codebases. Read the paper: https://lnkd.in/gFMgN7nT
About us
From conducting fundamental research to influencing product development, our research teams have the opportunity to impact technology used by billions of people every day. We aspire to make discoveries that impact everyone, and sharing our research and tools to fuel progress in the field is fundamental to our approach.
- Website
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https://research.google/
External link for Google Research
- Industry
- Technology, Information and Internet
- Company size
- 1,001-5,000 employees
Updates
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How can we enable coherent, long-form video storytelling with AI? Catch Yale Song and Yiwen Song at the #COLM2026 Google booth #107 today at 1:00 PM PT for an interactive demo of Co-Director — a hierarchical multi-agent framework optimizing video generation and consistency. Join us to see interactive cinematic narratives in action! Read the blog: https://lnkd.in/eumEF3QG
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Google is proud to be a Diamond Sponsor of the Conference on Language Modeling (COLM 2026)! Join us at the Hilton Union Square in San Francisco from Oct 6–9 as researchers from Google Research and @GoogleDeepMind present 28 papers and participate in 16 workshops. Attending #COLM2026 in person? Stop by Google booth #107 to explore our latest innovations in agentic systems, reasoning, and multimodal AI. Learn more: https://goo.gle/COLM2026
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Today we share the results of five partner-driven case studies demonstrating how Google Earth AI's Population Dynamics Foundation Model addresses public health data gaps, empowering global health research. Read the blog to learn more: goo.gle/46YAvqT
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Announcing the Gemma 4 Developer Agent Competition! 🚀 Don't miss the opportunity to compete for a $100K prize pool by November 25, 2026. The challenge: post train an open model into a coding agent capable of speeding up developer workflows on standard, everyday hardware. It’s a chance to showcase: - Using fine-tuning and reinforcement learning to sharpen SWE (software engineering) agent capabilities - Innovative approaches for parsing, embedding, and reasoning through complex codebases - New tasks, datasets, and tools that support structured code generation Competition Track: https://lnkd.in/epVjTHep Paper Track: https://lnkd.in/gT88cwfP
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Today we’re introducing a next-generation Federated Learning system. By using Trusted Execution Environments (TEEs), it delivers verifiable differential privacy while moving computation server-side to cut training times. Read the blog: goo.gle/4ynJTAd
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Today the Centers for Disease Control and Prevention announced that of 39 eligible models, Google's science AI model ranked highest for forecasting flu-related hospital admissions during the 2025-26 flu season. Google's forecasts were developed using Empirical Research Assistance, an AI tool that generates computational solutions across a range of scientific fields. Learn more: https://goo.gle/4hFJrq9
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Introducing Diffusion Controller, a lightweight steering damper that precisely steers image generation for better prompt alignment without breaking stability. Read the blog to learn how it boosts image quality without breaking baseline stability → goo.gle/46Sx7O8
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Today we announce our new unified multi-agent framework that provides creators with a system for generating temporally consistent, long-form video narratives while mitigating visual drift and pipeline error propagation. Learn more: goo.gle/4AxvXFh
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How does an Academy Award winner with two named asteroids build AI for science? In the latest Latent Space podcast episode, Google’s John Platt discusses: • Fighting climate change with AI, from airplane contrail reduction (those little white lines behind planes that contribute ~1% of human-caused warming) to fire detection with FireSat satellites. • Google helping pioneer the application of data to track disease progression, and how that journey has come full circle: our research team's Empirical Research Assistance (ERA), using Gemini and Monte Carlo Tree Search, achieved top marks in recent CDC benchmarks for forecasting COVID and flu cases a week in advance. • How the field of AI in science has evolved and what lessons he's learned. • His advice for young scientists, including his own son. Listen to the full episode: https://lnkd.in/gjP9Km2M
🔬 Google's AI Scientist Started as an Attempt to Automate Kaggle — John Platt, Google Fellow
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