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AI at Meta

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@AIatMeta

We're building the future of personal superintelligence to help people create, connect, and achieve more in life.
ai.meta.com Joined August 2018
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Latest posts 5

AI at Meta Verified account @AIatMeta
Today we're bringing specialized models trained using Muse Wonder to @Muse and Meta AI, giving users access to some of Muse Wonder's frontier capabilities for complex tasks at work and in everyday life.

These specialized models include Muse Wonder's Active Memory and Active Focus, helping them stay aligned with your goals as tasks unfold:

→ Active Memory helps recognize when earlier information matters and distinguish what's still relevant from what's become stale

→ Active Focus helps recover from setbacks or find alternatives when constraints change

In Muse, the improved models show a 2.4x reduction in forgetting information critical to your goals and a 67% improvement in getting unstuck as constraints evolve. That means less repeating yourself and fewer dead ends when plans change.

In Meta AI, these improvements help it break complex problems into steps, ask sharper follow-up questions and adapt when you change direction.

Read more on our research blog: go.meta.me/4kCPcHW
111 replies 101 reposts 681 likes 83K views View on X
AI at Meta Verified account @AIatMeta
During Connect, we previewed Muse Realtime Avatar, our real-time embodiment technology that turns Muse Realtime Voice into expressive, interactive avatars.

Today, we’re rolling it out in the @Muse app in the US, giving people a more natural way to engage with their personal agents.

Learn more about Muse Realtime Avatar on our research blog: go.meta.me/47ZSNso
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100 replies 46 reposts 419 likes 66K views View on X
AI at Meta Verified account @AIatMeta
Today we're announcing support for university research at @Caltech, @OhioStateMed, @LSU, @IndianaUniv, and @UTHealthHouston to help advance breakthroughs across science and medicine.

As part of the support for university researchers, we’ll provide access to our latest Muse models, including Muse Wonder and Muse Spark; open weight models like Muse Glimmer and Muse Spark Open; computer vision models such as SAM, V-JEPA, and DINO; as well as SeamlessM4T, our multilingual communication model.

We’re excited to support these five universities as they use our models to accelerate the important work they’re doing.

Read more on our research blog: go.meta.me/47G6wV3
52 replies 37 reposts 239 likes 53K views View on X
AI at Meta Verified account @AIatMeta
Today we published a technical report on Muse Glimmer, our 30B open-weight model built for agentic tasks on consumer hardware.

It runs at practical speeds on a Mac or PC with a single consumer GPU at 4-bit precision, and leads comparably-sized open models on tool use and multi-step planning.

Read about the model architecture, distillation recipe, quantization and more: go.meta.me/4Bcvxol
186 replies 187 reposts 1.4K likes 236K views View on X
AI at Meta Verified account @AIatMeta
We trained our Muse foundational models, including Muse Wonder, at Prometheus, our gigawatt-scale supercluster in New Albany, Ohio.

Across a supercluster with hundreds of thousands of GPUs, even one underperforming host can slow an entire training run. We engineered Prometheus for resilience at scale, achieving 85%+ goodput on pretraining, 90%+ on reinforcement learning and ~47K GPU hours mean time between interruptions during Muse Wonder training.

Take a look at the tech powering Prometheus: go.meta.me/4yXXApZ
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