Charles Sutton @RandomlyWalking

Excited to launch Google Antigravity, our next generation agentic IDE, now powered by Gemini 3!

Gemini 3 is finally out. 🚀 The numbers on the hardest benchmarks are wild. Seeing MathArena Apex go from <2% to 23.4% and ARC-AGI-2 hit 31% feels like a real turning point for reasoning. We're starting to crack problems that used to look impossible. Huge congrats to the team.

We’re excited to see the security and OSS communities engage on vulnerability disclosure in light of new AI technologies that we believe will enable both defenders and attackers alike. Existing and emerging norms around disclosure are important debates, and we’ve noted the feedback. Thanks! Also want to share some additional thoughts. 1/10

I am pleased to announce our new paper, which provides an extremely sample-efficient way to create an agent that can perform well in multi-agent, partially-observed, symbolic environments. The key idea is to use LLM-powered code synthesis to learn a code world model (in the form of Python code) from a small dataset of (observation, action) trajectories, plus some background information (in text form), and then to pass this induced WM, plus the observation history, to an existing solver, such as (information-set) MCTS, to choose the next action.

Initial results from a large scale run of @Google Big Sleep are here!Our AI agent found a series of vulnerabilities in widely used & reviewed software,demonstrating a new frontier in automated vulnerability discovery.Full details once the issues are fixed: goo.gle/bigsleep

Today as part of our commitment to transparency in this space, we are proud to announce that we have reported the first 20 vulnerabilities discovered using our AI-based "Big Sleep" system powered by Gemini — goo.gle/bigsleep

@scuzzlebot @YiyuanLi1 In my experience, actual gardening requires a combination of extensive knowledge (sounds interesting) and hard manual labor (not a fan). Metaphorical gardening is much less taxing.

New blog! Advice about career and creativity for researchers and engineers. This time: What my PhD in computer science taught me about gardening. theexclusive.org/2025/07/phd-ga…

Back in grad school, when I realized how the “marketplace of ideas” actually works, it felt like I’d found the cheat codes to a research career. Today, this is the most important stuff I teach students, more than anything related to the substance of our research. A quick preface: when I talk about research success I don’t mean publishing lots of papers. Most published papers gather dust because there is too much research in any field for people to pay attention to. And especially given the ease of putting out pre-prints, research doesn’t need to be officially published in order to be successful. So while publications may be a prerequisite for career advancement, they shouldn’t be the goal. To me, research success is authorship of ideas that influence your peers and make the world a better place. So the basic insight is that there are too many ideas entering the marketplace of ideas, and we need to understand which ones end up being influential. The good news is that quality matters — other things being equal, better research will be more successful. The bad news is that quality is only weakly correlated with success, and there are many other factors that matter. First, give yourself multiple shots on goal. The role of luck is a regular theme of my career advice. It’s true that luck matters a lot in determining which papers are successful, but that doesn’t mean resigning yourself to it. You can increase your “luck surface area”. For example, if you always put out preprints, you get multiple chances for your work to be noticed: once with the preprint and once with the publication (plus if you’re in a field with big publication lags, you can make sure the research isn’t scooped or irrelevant by the time it comes out). More generally, treat research projects like startups — accept that there is a very high variance in outcomes, with some projects being 10x or 100x more successful than others. This means trying lots of different things, taking big swings, being willing to pursue what your peers consider to be bad ideas, but with some idea of why you might potentially succeed where others before you failed. Do you know something that others don’t, or do they know something that you don’t? And if you find out it’s the latter, you need to be willing to quit the project quickly, without falling prey to the sunk cost fallacy. To be clear, success is not all down to luck — quality and depth matter a lot. And it takes a few years of research to go deep into a topic. But spending a few years researching a topic before you publish anything is extremely risky, especially early in your career. The solution is simple: pursue projects, not problems. Projects are long-term research agendas that last 3-5 years or more. A productive project could easily produce a dozen or more papers (depending on the field). Why pick projects instead of problems? If your method is to jump from problem to problem, the resulting papers are likely to be somewhat superficial and may not have much impact. And secondly, if you’re already known for papers on a particular topic, people are more likely to pay attention to your future papers on that topic. (Yes, author reputation matters a lot. Any egalitarian notion of how people pick what to read is a myth.) To recap, I usually work on 2-3 long-term projects at a time, and within each project there are many problems being investigated and many papers being produced at various stages of the pipeline. The hardest part is knowing when to end a project. At the moment you’re considering a new project, you’re comparing something that will take a few years to really come to fruition with a topic where you’re already highly productive. But you have to end something to make room for something new. Quitting at the right time always feels like quitting too early. If you go with your gut, you will stay in the same research area for far too long. Finally, build your own distribution. In the past, the official publication of a paper served two purposes: to give it the credibility that comes from peer review, and to distribute the paper to your peers. Now those two functions have gotten completely severed. Publication still brings credibility, but distribution is almost entirely up to you! This is why social media matters so much. Unfortunately social media introduces unhealthy incentives to exaggerate your findings, so I find blogs/newsletters and long-form videos to be much better channels. We are in a second golden age of blogging and there is an extreme dearth of people who can explain cutting-edge research from their disciplines in an accessible way but without dumbing it down like in press releases or news articles. It’s never too early — I started a blog during my PhD and it played a big role in spreading my doctoral research, both within my research community and outside it. Summary * Research success doesn’t just mean publication * The marketplace of ideas is saturated * Give yourself multiple shots on goal * Pick projects, not problems * Treat projects like startups * Build your own distribution

@YiyuanLi1 Thanks for catching the typo! My take: Weeds are plants that are unwanted. If you like them, they are no longer weeds!

@Stefania_druga I haven’t! Thanks for the recommendation!

I’m excited to share the news of Gemini Deep Think’s gold-medal level performance 🥇 at the International Math Olympiad! It has been an absolute blast building Deep Think this year and then scaling it to the IMO.

Google DeepMind @GoogleDeepMind

11 months ago

An advanced version of Gemini with Deep Think has officially achieved gold medal-level performance at the International Mathematical Olympiad. 🥇 It solved 5️⃣ out of 6️⃣ exceptionally difficult problems, involving algebra, combinatorics, geometry and number theory. Here’s how 🧵

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@y0b1byte Haha, you found that fast! Thanks for the kind words!

Great post by @RandomlyWalking

@YiMaTweets And what was your answer?

New from our security teams: Our AI agent Big Sleep helped us detect and foil an imminent exploit. We believe this is a first for an AI agent - definitely not the last - giving cybersecurity defenders new tools to stop threats before they’re widespread.

Very excited to share this update about our team's work on AI for security! Joint work with @miltos1 @xennygrimmato_ @dancherp and many others from GDM and Google Project Zero! To learn more about our agent Big Sleep, check out this blog post: googleprojectzero.blogspot.com/2024/10/from-n…

Sundar Pichai @sundarpichai

11 months ago

New from our security teams: Our AI agent Big Sleep helped us detect and foil an imminent exploit. We believe this is a first for an AI agent - definitely not the last - giving cybersecurity defenders new tools to stop threats before they’re widespread.

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Together with the Big Sleep team, I discovered the first in-the-wild 0-day using an AI agent. Go patch your boxes! cve.org/cverecord?id=C…

Sundar Pichai @sundarpichai

11 months ago

New from our security teams: Our AI agent Big Sleep helped us detect and foil an imminent exploit. We believe this is a first for an AI agent - definitely not the last - giving cybersecurity defenders new tools to stop threats before they’re widespread.

247 789 9K 746K 908

🔔 Announcing our paper on Natural Language Outlines for Code! Our vision 🔮 - NL Outlines empower human developers with new forms of AI assistance throughout the software development process 🚀 Paper: arxiv.org/abs/2408.04820 FSE'25 presentation: youtube.com/watch?v=54v7Zp… 🧵👇

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🚀 Really excited to launch #AgentX competition hosted by @BerkeleyRDI @UCBerkeley alongside our LLM Agents MOOC series (a global community of 22k+ learners & growing fast). Whether you're building the next disruptive AI startup or pushing the research frontier, AgentX is your launchpad. Two tracks: - Entrepreneurship: Build agent-powered products & startups - Research: Explore the frontiers of LLM Agents technology 📅 Registration opens TODAY! Submissions due end of May 🏆 Winners showcase at our Agents Summit to industry leaders and VCs in August @UCBerkeley! 🌟 🙏 Tremendous thanks to our incredible sponsors @Amazon @huggingface @LambdaAPI @MistralAI @Google @GroqInc @schmidtsciences; proud to partner w. leading VCs in the space @Accel @BainCapVC @BessemerVP @lightspeedvp @MayfieldFund @NEA! Stay tuned—more sponsors/partners AND exciting prizes/credits/resources info will be announced soon! 🚀 ⏰ Register now at rdi.berkeley.edu/agentx/ and join us in shaping the future of AI! #AgentX #AI