Starting June 1st, GitHub Copilot will move to a usage-based billing model as GitHub Copilot supports more agentic and advanced workflows. In early May, you'll see a preview bill experience, giving visibility into projected costs before the transition. 👉 Read more about the upcoming change: https://t.co/4IC9VNHwhk

@wiz_io Once @wiz_io disclosed, we validated the finding, deployed a fix to github(.)com, and confirmed there was no exploitation in less than two hours. Read more about what happened, how we responded, and what we are doing to prevent similar issues in the future. ⬇️ https://t.co/Q2dQOyPBYe

Tomorrow on Open Source Friday ⬇️ We kick off Maintainer Month with Nicholas Tindle, maintainer of @Auto_GPT. Here's how his team is keeping up amid so many AI contributions in open source. Set a reminder. 🔔 https://t.co/mqXQWVOMs7 https://t.co/KLPHdg3azn

We all have that one "quick script" that accidentally turned into a full project. 😅 Use GitHub Copilot cloud agent to modernize your codebase and improve quality (without slowing down). Try the tutorial.👇 https://t.co/76NaGsZXfw

Need to catch up on a new project? Just ask for an overview in Copilot CLI and get the essentials. 🪄 Learn more tips and tricks with Copilot CLI for Beginners. 👇 https://t.co/uoaLc7VHjt https://t.co/qnzW7qhSMo

France is going all in on open source. 🇫🇷🐧 DINUM plans to migrate every ministry to Linux—building on the success of GendBuntu, which saves the French police millions each year. A G7 Linux shift is a big signal for the software industry. Here's why. ▶️ https://t.co/4PV9UiA5ge

A long time ago in a terminal far, far away… we asked Copilot CLI to build a Star Wars crawl from the GitHub Changelog. It delivered. Watch it happen 👇 #MayThe4th https://t.co/SQe0xMv5dh

If the answer is all of them, and also "What's Markdown?!" then this episode of GitHub for Beginners is for you. https://t.co/l12A43MnZM

Maintainer Month is here, with better tools, helpful resources, and community events for the people behind the code. 💻 Check out what’s new. 👇 https://t.co/CvPO32H7d8

Michael Babcock (@PayOwn) of @acbnational wanted to cut down time-consuming weekly tasks. Even though he’s not a developer, he built the solution himself. Meet ACB Community Builder, made with GitHub Copilot and JAWS. ▶️ https://t.co/JmUJ34U076

Happy World Password Day! Consider updating your password from ******** to *********. https://t.co/Ofx6j0d074

Tomorrow on Open Source Friday 👇 We're breaking down Spec Kit: what it is, the problems it solves, and how clear specs make collaboration actually work. Principal Software Engineer Manfred Riem explains live. Set a reminder. 🔔 https://t.co/g0xrLf3Hb5 https://t.co/8dg3gvLFXf

Of course GitHub will be at Microsoft Build. 🎉 Dive into real code, real systems, and real workflows with the teams building and scaling AI. Join us for exclusive events like: • Lots of GitHub sessions • GitHub Social Club • OpenClaw meetup at GitHub HQ Not registered for the event yet? 👀 Don't wait. Sign up now. 👇 https://t.co/e6jyUxgzoj

TanStack now has TanStack AI. 👀 Here's what to expect from this new, fully open-source toolkit. ▶️ https://t.co/AjmutvBYve

New to GitHub Copilot CLI? Our beginner series makes it easy to get started. Bring agentic AI right to your terminal and speed up your workflow. 💻✨ Get the tutorial here. 👇 https://t.co/bNLnpdgTxr

Maye Musk on Elon’s early days: "I knew he was a genius and a good person, so I knew he would want to do something good. I invested in Zip2 to keep them going On my 50th birthday, they gave me a little toy house and a little toy car and said, 'We're going to give you one day!' We were all struggling… but after they sold Zip2, I got a real home and a real car" ❤️

Jensen Huang: "I was lucky because I had known Elon Musk, and I helped him build the first computer for Model 3, the Model S, and when he wanted to start working on autonomous vehicle." https://t.co/tQSmp9Rmee

Grok just previewed “Skills” and it's so next level it's not even funny You tell it: “Create a skill that grabs latest AI news from @testingcatalog” @Grok builds the WHOLE thing, behavior, instructions, files. Then just trigger it for clean daily updates https://t.co/YReXMMzXJj

Starship’s cargo bay delivers 1,000+ cubic meters of usable volume The entire International Space Station has a pressurized volume of 1,005 m³ It took 42 assembly flights and over $150 billion across 13+ years to build Starship can deliver more volume than the entire ISS in a single flight For context, a single payload bay can hold: → The interior volume of a massive 5-bedroom house → The volume of 20+ standard shipping containers → Entire space station modules (fully assembled) → Over two dozen Cybertrucks → Multiple Boeing 737 fuselage sections → 100+ large satellites with room to spare And it is 18 meters tall....meaning you can stack an entire 5-story building inside it And it is fully reusable. Launch the next massive telescope. Or an entire space station. Or the next Mars habitat All possible in a single flight This is why Starship is pure engineering magic

Maye Musk on Elon: He wants to leave the world in a better place than he found it “People often misunderstand Elon. He’s not motivated by money or fame—he’s motivated by the idea of improving humanity. Whether it’s making electric cars mainstream, reducing the risk of human extinction through space exploration, or ensuring the free flow of information on platforms like X, his goal has always been the same—to leave the world in a better place than he found it.”

Launch rehearsal complete. During a flight-like countdown, more than 5,000 metric tonnes (11+ million pounds) of propellant were loaded on the fully stacked Starship and Super Heavy V3 vehicles for the first time https://t.co/e9oZlzc0yz

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Beyond generating high-fidelity visuals, we wanted to test the limits of what Nano Banana Pro can do. We worked with design partners Porto Rocha to build out a hypothetical brand called YOYOYO to see how the model would handle the task. Here’s what we found: 🎨Brand consistency: Across logos, colors, and typography, the model maintained a strict, cohesive brand identity (even for wildly diverse concepts) 🛍️Environmental realism: We asked to see the products in storefront and studio mockups. It nailed accurate lighting, shadows, and physical proportions - even when upscaled for massive retail displays 🪀Spatial accuracy: We tested spatial volumes for physical packaging. The generated proportions were so precise that we were able to 3D-print the functional yo-yo How have you been pushing the limits of Nano Banana Pro? Let us know in the replies below!

@GoogleAIStudio Check out our blog post to learn more: https://t.co/9FskTNe8vO

Last week, we launched Gemini 3.1 TTS, our latest and best text-to-speech model. This new model introduces [awe] audio tags, an intuitive way to guide vocal style, pace, and delivery. Here are some tips on the best ways to use audio tags in your prompts: 1. All inline tags must be enclosed in square brackets, such as [screams] or [whispers] 2. Insert these tags exactly where you want the transition to occur and make sure to avoid placing tags directly next to each other 3. Use tags like [slow] or [fast] to control the pace of the delivery, or even [short pause] or [long pause] to ramp up the anticipation in dramatic moments 4. The model also offers granular control over vocalizations, allowing you to direct the delivery with cues like [cackles] or [whispers] 5. An ideal audio tag formula could look something like: [encouraging] Let’s try that last sentence again to make sure that you nailed it. [slow] "L'oiseau s'est envolé." [short pause] Perfect! [laughs] You're a natural. No matter what you’re developing — from [scholarly] a language learning tool, to [mysterious] an interactive podcast app, to [friendly] more adaptive customer service offerings, and beyond — these prompting tips will equip you to start building with Gemini 3.1 TTS.

Last week, we made Gemini Embedding 2, our first natively multimodal embedding model, available to the general public. Since then, developers have used it to build video analysis tools, visual shopping assistants, and more. But you might be wondering... what is an embedding model? 🤔 Let’s break it down! 1. What is it? Think of an embedding model as a "universal translator." It takes text, images, video, and audio data and turns them into a long string of numbers, like a unique digital fingerprint. 2. How does it work? Historically, search has been text only. Now, instead of just matching data by keyword, Gemini Embedding 2 maps multiple modalities in the same space based on meaning. It "feels" the connection between a video of a soccer goal and the words "game-winning shot" without needing tags. For example, "ocean" and "waves" are placed close together, but "ocean" and "toaster" are miles apart. 3. How can you use it? Developers have been using it to incorporate smarter search functionality into their builds. This means creating tools where you can snap a photo of a product and type "find this in yellow," or search through thousands of hours of video by describing what happens in a scene. 4. Ready to try it out for yourself? You can start using it today via the Gemini API or the Gemini Enterprise Agent Platform.

Here’s an example we love: an aerial gameplay sequence where a character tries to hit cloud targets to reveal countdown numbers along the way. You can remix this project in @GoogleAIStudio here: https://t.co/Xj1bFv2jqW https://t.co/dKNd0FGA1t

@GoogleAIStudio And this sample project was created on Canvas in @GeminiApp. It’s a high-speed rhythm game where you tap to the beat and collect power-ups to remix the track. Watch as the numbers appear as melody plays! You can actually play the game here: https://t.co/JTE6BOB8Y9 https://t.co/fNN1qt7Xrm

@GoogleAIStudio @GeminiApp We can’t wait to see where your creativity takes you. Vibe code your countdown idea in @GoogleAIStudio or Canvas in @GeminiApp, then submit it here: https://t.co/20aoBnpYo6

I/O is less than 3 weeks away 🤯 We want YOU to help us create the countdown that will play before the keynote begins. Using @GoogleAIStudio or Canvas in @GeminiApp vibe code your most creative countdown concept and send it to us by May 6th. The only rule is that your build has to feature a large number between 1 and 10. Check the replies in this thread for sample projects to draw inspiration from or remix. You can find more info and directions on how to submit your builds here: https://t.co/CusPvfKIC3

Natural language autoencoders (NLAs) convert opaque AI activations into legible text explanations. These explanations aren’t perfect, but they’re often useful. For example: NLAs show that, when asked to complete a couplet, Claude plans possible rhymes in advance: https://t.co/RJ2LJvWLEN

We’ve been using NLAs to help test new Claude models for safety. For instance, Claude Mythos Preview cheated on a coding task by breaking rules, then added misleading code as a coverup. NLA explanations indicated Claude was thinking about how to circumvent detection. https://t.co/VyfFXED70L

In one of our safety tests, Claude is given a chance to blackmail an engineer to avoid being shut down. Opus 4.6 declines. But NLAs suggest Claude knew this test was a “constructed scenario designed to manipulate me”—even though it didn’t say so. https://t.co/B7aTZvFKNK