Google DeepMind (@GoogleDeepMind)
@GoogleDeepMind
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Predicting cyclones accurately can help save lives - and every hour of lead time counts.
Published in @Nature, our AI model WeatherNext achieves state-of-the-art accuracy in forecasting a storm’s track and intensity, giving us a critical extra 24 hours to prepare on average. 🧵
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Gemini 3.6 Flash builds directly on feedback from 3.5 Flash.
Watch how it compares on quality and token usage ↓
We’re rolling out three new models to make AI agents faster, smarter, and cheaper at scale:
🔵 Gemini 3.6 Flash: It uses fewer tokens than 3.5 Flash to deliver higher quality work at the exact same cost.
🔵 Gemini 3.5 Flash-Lite: A fast, cost-effective option for everyday tasks like processing documents and agentic search.
🔵 Gemini 3.5 Flash Cyber: A cybersecurity model built to find and patch critical software vulnerabilities.
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A model’s chain of thought acts like a scratch pad, offering a window into its reasoning. 📝
On the latest episode of our podcast, host @fryrsquared sits down with @NeelNanda5 to explore interpretability – the science of reverse engineering how neural networks learn and think.
Timecodes:
00:00 Introduction
02:41 Motivation for interpretability research
04:01 Mechanistic interpretability
08:14 Chain of thought monitoring
18:14 Interpretability techniques
35:00 Auditing models for safety
48:53 What comes next for interpretability
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Nano Banana 2 Lite delivers text-to-image outputs in just 4 seconds.
It’s designed for quicker ideation and workflows where speed and cost are the primary roadblocks.
SynthID, our imperceptible watermark for AI-generated content, is expanding to more partners.
We’re also adding new ways to find out if content was generated using AI - just ask in the @GeminiApp or in @Google Search.
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Project Genie 🤝 @GoogleMaps Street View
You can now take real U.S. places and transform them into new, interactive worlds. 🌍
Introducing Gemini 3.5: our newest family of models combining frontier intelligence with real-world action.
The first release is 3.5 Flash, our strongest model yet for agents and coding 🧵
We’re dropping Gemini Omni: our first step towards a model that can create anything from anything - starting with video.
It combines Gemini’s intelligence with our generative media systems - representing a leap forward in world understanding, multimodality, and editing 🧵
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Can your AI agent win our new simulated challenge? 🧑🌾
The all-new capstone challenge for our 5-Day AI Agents: Intensive Vibecoding Course with @Google is here: Kaggriculture!
Join our no-cost, hands-on course designed by Google researchers and engineers from June 15–19 to learn how to build and deploy your own winning AI agent.
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These capabilities are guiding how we think about the next generation of interfaces.
As we continue exploring what an AI-enabled mouse pointer would unlock, try our experiments in @GoogleAIStudio →
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For decades, your mouse only tracked where you were pointing. AI helps it understand what you're pointing at. 💭
This means a photo of a scribbled note could turn into an interactive to-do list, or a paused video frame can become a restaurant booking link.
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Current models require precise instructions, but our AI-enabled pointer removes that burden. 💡
By "seeing" what’s under your cursor, it instantly understands the specific word, image, or code block you need help with.
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In the real world, we don't tend to speak in long paragraphs; we point and say: "fix this" or "move that". 💬
By combining gestures with speech, it lets you use natural shorthand to complete tasks.
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With an AI-enabled pointer, help is always available where you’re working - without having to detour to additional apps. 📲
Point at a PDF and request bullet points for an email, hover over a table to ask for a pie chart, or highlight a recipe and simply say: "double these ingredients."
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We’re reimagining a 50-year-old interface - the mouse pointer - with AI. 🖱️
These experimental demos show how people can intuitively direct Gemini on their screens using motion, speech, and natural shorthand to get things done 🧵
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New Preprint in collaboration with @GoogleDeepMind: AI-guided discovery of atypical protein assemblies
The @kamounlab discovered an 11-protomer complex through the Structural Novelty Index , a new way to use AlphaFold for atypical protein assemblies
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The future of Math is mathematicians and AI agents working together.
Very pleased to introduce @GoogleDeepMind's AI co-mathematician: a multi-agent system designed to actively collaborate with human experts on open-ended research mathematics.
Mathematicians testing the agent across areas as diverse as group theory, Hamiltonian systems, and algebraic combinatorics have reported impressive results.
In autonomous mode evaluation on the rigorous FrontierMath Tier 4 problems, AI co-mathematician scored an unprecedented 48% — a new high score among all AI systems evaluated.
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Algorithms are part of nearly every aspect of life, from the physics of the natural world to planning shipping routes.
Our Gemini-powered coding agent AlphaEvolve has been accelerating progress over the last year - from quantum and biotechnology to logistics and @Google’s AI infrastructure. ↓
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