We sat down with @GoogleResearch scientist, Deborah Cohen, to learn about the Google Flood Forecasting Initiative and how our AI models work to help forecast floods and keep communities safe.

New @Nature publication from @GoogleResearch & @GoogleDeepMind: In this study, we advance AMIE, our research medical AI, from one-off diagnostic conversations toward treating & managing disease over time, using clinical guidelines & drug formularies. More:

Introducing WeatherNext 3! Built by @GoogleDeepMind and @GoogleResearch, this is our most advanced & accurate AI weather model, and now includes real-time satellite data, hourly refreshes, higher resolution, precise precipitation forecasting, and clean energy variables. Read the blog: Build with WeatherNext 3: More about Google Earth AI for planetary intelligence:

At #GoogleIO#, we announced Gemini for Science, a collection of new experimental tools developed by @GoogleResearch, @GoogleLabs, @GoogleDeepMind & @GoogleCloud. Learn more about how we’re supercharging scientific research:

How can we help scientists get better data out of their instruments? Using @GoogleDeepMind AlphaEvolve, @GoogleResearch identified new ways to train DeepConsensus, improving DNA sequencing accuracy and output on PacBio instruments. Read more:

Attending the Women in Machine Learning (WiML) Social at #ICLR2026#? Stop by 203C from 12PM - 3PM to connect with the community and the Google Research team! #WiML# #GoogleResearch#

Welcome to #ECCV2026#! 🌟 Google is proud to be a Diamond Sponsor at @eccvconf in Malmö, Sweden (Sept 10–12). Visit us at booth #2# to explore our latest research, connect with our team, and see live demos! Learn more: #GoogleResearch#

Check out this week’s shipping recap: — Gemini 3.8 Flash, our most intelligent workhorse model yet, delivers upgrades across coding, agentic workflows, and critical multi-step reasoning. — Gemini 3.8 Flash Cyber, our most capable cybersecurity model, features frontier-level performance in vulnerability detection and automated patching. — Lyria 3.5, our newest music generation model, is now available via the Gemini API, and across @GoogleAIStudio, @GeminiApp, @FlowbyGoogle, and Google Vids. — WeatherNext 3, our most advanced and accurate global weather AI model, is here from @GoogleDeepMind and @GoogleResearch. — Agentic Video Understanding, our new video analysis feature available via the Gemini API in @GoogleAIStudio and the Gemini Enterprise Agent Platform, improves accuracy while dramatically reducing token usage and costs.

Google Research's Yossi Matias says their flood model learns from the places that have data and then predicts for the places that don't: "We published a paper in Nature with what we call Global Hydrologic Model." "And really what we showed is that we can actually build models that are learning from flood events in places that we have enough data, and then apply it also to places that we don't have as much data." "And what started as an impossible problem, quote unquote, we actually now not only showed that we can drive the science, but also the same team, we've built a system that now provides up to seven days prediction in 150 countries covering 2 billion people." "So it's already life-saving because it's out there, it's available for responders, for governments through what we call a flood hub." "And you know, just a few months ago, we had the government of Nigeria and organizations called GiveDirectly actually use an API to our flood hub to actually send money to villagers so they can evacuate ahead of time." He is a Google executive describing Google's own system, and the seven-day, 150-country, 2-billion-person figures are the company's. The hard part is that the rivers which flood most destructively are often the least instrumented, so a forecast is needed exactly where there is no local record to build one from. And a prediction only counts when something acts on it: here that was an API call moving cash to households before the water arrived, not a dashboard someone had to notice. - Yossi Matias, VP, Google and GM, Google Research, on The Google Research Podcast (@GoogleResearch).

Google Research and HHMI Janelia have digitally reconstructed the complete brain and central nervous system of an adult male fruit fly—more than 166,000 neurons and 125 million synaptic connections. This does not mean that a fruit fly’s consciousness has been uploaded. A connectome is not memory, and it is certainly not life itself. But an important boundary has been crossed: a nervous system is moving from something we can only observe to a digital structure that computers can read, simulate, and experiment with. Today, it is a fruit fly. In the future, we may not only design artificial intelligence—we may also reconstruct and recombine natural intelligence. The boundary between silicon-based and carbon-based intelligence may become much less distinct than we imagine. So beyond making it play games, feeding it sensory stimuli, helping it survive—or letting it trade crypto—what other practical experiments should we try?