Google DeepMind (@GoogleDeepMind)
@GoogleDeepMind
The engine room of @Google. Building AI safely and responsibly to solve the world’s most complex problems. Join us:
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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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We’re partnering with the developers of @EveOnline to explore the next frontier of AI research in games.
EVE's complex, player-driven universe is the perfect safe sandbox to test agents on memory, continual learning, and long-term planning.
Find out more →
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Things to keep in mind:
✅ Base your creations around the numbers 1-10
✅ Use Canvas in @GeminiApp or @GoogleAIStudio
Submit by May 6 →
Think your vibe coding and creativity could be on the #GoogleIO# main stage? Show us.
As we countdown to the start of the show, the best ideas built with @GeminiApp or @GoogleAIStudio will be featured – think protein simulators, physics engines, or math-based art. 🔢
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One of @GoogleDeepMind's key aims is to unlock scientific progress on problems important for society.
Generating clean energy is one of the biggest challenges of our time, and technologies like nuclear fusion could be the answer. While we continue to conduct our own research on this problem, our team has also been talking to experts across the field to understand the main AI opportunities and data obstacles, and to share recommendations to unlock faster progress.
This kind of ‘AI Data Stocktake’ exercise can serve as a blueprint that policymakers, science funders, and industry can apply to many other scientific domains.
Read more at:
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We’re advancing this research with academics and institutions globally, and will gradually expand our clinician-facing trusted tester program to additional sites - to understand more perspectives of health workers and patients worldwide.
Find out more →
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To keep patient safety at the forefront, the system also runs on a dual agent architecture.
A built-in "Planner" continuously monitors the conversation verifying that the "Talker" agent stays within safe clinical boundaries.
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In testing, AI co-clinician matched or outperformed physicians in 68 out of 140 assessed areas, including triage.
Yet humans were easily better at spotting crucial red flags and guiding physical exams - showing how these tools could augment clinical judgment. See the benchmarks ↓
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Our research goal for AI co-clinician is to support medical decision making with high-quality evidence.
We tested the system while adapting the NOHARM safety framework, and found it made zero critical errors in 97 of 98 primary care queries - outperforming comparable systems in blind evaluations.
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The system uses live video and audio to process physical symptoms in real-time. This means it could analyze a patient's walk, listen to their breathing, or look at how a rash is appearing.
Alongside physicians from @Harvardmed and @StanfordMed, we created a simulation study with 20 scenarios and “patient-actors”. Watch how AI co-clinician reasons and diagnoses. ↓
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AI co-clinician is our new research initiative to help explore how multimodal agents could better support healthcare workers and patients. 🩺
Here’s a snapshot of our progress 🧵
