Introducing Muse, a personal agent that gets things done for you, powered by Muse Spark 1.3. Get an inside look at how we built Muse and what it can do for you: introducing.muse.ai/

In the past 6 months... - Muse Spark - Muse Image - Muse Video - Muse Spark 1.1 - Meta Model API - Muse Glimmer - Muse Spark 1.2 - Muse Code - Muse Spark 1.3 - Muse ...and we’re just getting started. 🚀

Come and build the future of superintelligence at the Meta Global AI Developer Hackathon. Ten days, access to our newest models and $1M in prizes. It’s virtual, worldwide and free to enter. Be the first to know when applications open → bit.ly/4jgQp7e

RT @MetaforDevs: Meta Connect 2026: Developer State of the Union x.lingyaoai.com/i/broadcasts/1pKkOXLDQ…

Meta’s Segment Anything Model (SAM) 3.1 is now available on Meta Model API, giving developers a fast and lightweight model for detection, segmentation and tracking in a single call on inference tuned for SAM 3.1's architecture. Use a short phrase to find objects in images and video. One API call returns detections, pixel-precise segmentation masks, and identity-preserving video tracks. Learn more and start building: bit.ly/4rDArq9

Muse Code from Meta is now available natively on Windows - no WSL required. It’s PowerShell-fluent, sandboxed by default, native x64 and ARM64, and supports zero-admin install. Coming soon: intersession messaging. Get started: irm dev.meta.ai/install.ps1 | iex Learn more: bit.ly/3UZJhlA

Last month I wrote about how we can build a positive and safe future for everyone: meta.com/thefutureisforevery… Every lab has the responsibility and incentive to move at the pace required to train its models safely, and the ability to take its own actions to ensure that happens. The reality is: - People won't want to use agents that are misaligned with them and that don't do what they ask, so labs have a strong natural incentive to make their models more aligned. There is a lot of debate about slowing progress on capabilities until alignment catches up. My view is that trust and alignment are quickly becoming the most important capabilities that will differentiate agents and models. Any lab that doesn't focus on alignment will fall behind. - Labs face significant liability if their models cause harm, so they have a strong incentive to prevent this as well. Meta delayed shipping Muse for several months to focus on safety and security. We didn't call for everyone else to do this before we would. We just did it as part of our day-to-day work because it was clearly the right thing for people and for us. I'm proud of the security foundations we've built. - Engaging independent evaluators and advisors is industry best practice. MSL already does this today in several areas because it helps produce better work. Other labs can just do this too. In general, it would be helpful for there to be a larger and more diverse ecosystem of evaluators. - Committing the significant majority of compute towards serving people rather than racing towards recursive self-improvement is one of the best ways to ensure we develop this technology safely. Meta has made this commitment and other labs can do this as well. I believe the key to building a positive future for everyone is maintaining the right balance of power. This is within our power to do.

Today, w/ Andrew Ferguson's group at @UChiPritzker: we're able to simulate entire enzyme systems with explicit solvent (O(100k) atoms) at near-quantum accuracy, matching real experimental measurements for enzyme activity. ~1,000x faster than SOTA QM/MM.

BREAKING: Muse Spark 1.3 (xhigh) takes 1st overall on Website Arena with an Elo of 1362! This is a jump of 5 positions from Muse Spark 1.2, establishing a new Pareto frontier for Speed and Price. Only a month after the release of Muse Spark 1.2, @AIatMeta has topped this category on Design Arena. Note: GPT-6 Astra is still pending final results. Congrats to the @Meta team!