Google DeepMind (@GoogleDeepMind)
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Meet Gemini 4 Hydrogen: built for rapid coding, multimodal synthesis, and everyday workflows.
It finishes tasks 2.5x faster than 3.8 Flash and surpasses Argon on the @ArtificialAnlys Intelligence Index.
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Gemini Robotics 2.5 is here. 🤖
Our latest physical AI is able to learn hundreds of everyday skills - from folding laundry and serving pastries to autonomously sorting car parts on the factory floor.
Here’s a snapshot of its capabilities 🧵
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SynthID Detector is now available to everyone. 🌐
Check whether online content was generated using @GoogleAI, or with tools from our industry partners – including @OpenAI, @NVIDIA, Kakao and coming soon, @Apple.
Try it out →
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Meet EmbeddingGemma 2, our first natively multimodal open model for on-device embeddings.
It expands beyond text to unify code, images, audio, and video in a shared space. 🧵
SynthID Bio is our new family of watermarking methods made for AI-generated biological designs.
In a world first, we can now embed an imperceptible signature directly into protein sequences without affecting their biological function. 🧵
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Introducing Gemini 4 Argon – our new frontier model.
It’s built for complex workflows across coding, enterprise knowledge work, and cybersecurity defense – rolling out today to a set of trusted testers through our Fairwind Program.
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Gemini 3.7 Flash is here.
It’s stronger for coding, knowledge work, and web development. 🧵
We sat down with Apollo 2 to talk about what it's really like running on Gemini Robotics 2. 🤖
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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