AI at Meta(@AIatMeta)

Today we launched https://t.co/KLJSHpx0pZ, a personal AI agent, and published a deep dive on how we ...

AI at Meta (@AIatMeta) — Tue, 08 Sep 2026 19:27:22 GMT

Today we launched muse.ai, a personal AI agent, and published a deep dive on how we built safety into its system.

An agent that gets to know you over time necessarily holds a lot of context about you. That's the source of its usefulness and the reason we built Muse to be secure, safe, and private.

Read the full deep dive here: security.muse.ai

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Today we launched https://t.co/wErICEYbFU, a personal AI agent, and published a deep dive on how we ...

AI at Meta (@AIatMeta) — Tue, 08 Sep 2026 19:18:32 GMT

Today we launched Muse.ai, a personal AI agent, and published a deep dive on how we built safety into its system.

An agent that gets to know you over time necessarily holds a lot of context about you. That's the source of its usefulness and the reason we built Muse to be secure, safe, and private.

Read the full deep dive here: security.muse.ai

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Introducing Muse, a personal agent that gets things done for you, powered by Muse Spark 1.3. Get an...

AI at Meta (@AIatMeta) — Tue, 08 Sep 2026 19:07:38 GMT

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

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While the Kaggle competition demonstrated AIRA₃’s capabilities in a specific domain, the system itse...

AI at Meta (@AIatMeta) — Sat, 05 Sep 2026 16:17:40 GMT

While the Kaggle competition demonstrated AIRA₃’s capabilities in a specific domain, the system itself can  generalize across distinct domains: changing only the task specification. In an internal benchmark, AIRA₃ achieved a 27% latency reduction on production GPU kernels, and gold-level performance in another Kaggle competition translating 4,000-year-old Akkadian clay tablets into English.

We're early, and hard problems are still ahead of us. But we believe a system that compounds its own knowledge is the right bet. As we continue to develop and scale, we’re excited about its potential to accelerate AI research and unlock recursive self-improvement.

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Rather than relying on a central controller, AIRA₃ runs many long-running agents (pairs of models + ...

AI at Meta (@AIatMeta) — Sat, 05 Sep 2026 16:17:39 GMT

Rather than relying on a central controller, AIRA₃ runs many long-running agents (pairs of models + coding harnesses) in their own isolated environments and coordinates asynchronously through two shared substrates:

1️⃣ a forum for sharing hypotheses and findings
2️⃣ a shared filesystem for solution artifacts

The individual agents collaborate, share discoveries, and build on each other’s work. As the graph below demonstrates, the system uses compute to compound knowledge and drive performance gains over time. Search strategies emerge dynamically as each agent decides which discoveries to build upon.

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We entered AIRA₃ with an ensemble of models in the live competition, and also assessed it with sever...

AI at Meta (@AIatMeta) — Sat, 05 Sep 2026 16:17:38 GMT

We entered AIRA₃ with an ensemble of models in the live competition, and also assessed it with several others post-hoc. The 8th ranked gold medal entry ensemble was a combination of GPT 5.5 (w/ OpenCode) + Claude 4.8 (w/ ClaudeCode).

Post-hoc we assessed with Muse Spark 1.2 (w/ MuseCode), which also performed at a Gold Medal level, as well as Muse Spark 1.1 (w/ OpenCode) and GLM 5.2 (w/ OpenCode), both of which achieved Silver Medal level performance. The post-hoc submissions were also graded externally on the same private test set as those made during the live competition.

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As a test of our progress to advance the frontier of AI research, in June we entered the next genera...

AI at Meta (@AIatMeta) — Sat, 05 Sep 2026 16:17:37 GMT

As a test of our progress to advance the frontier of AI research, in June we entered the next generation of our autonomous AI research system, AIRA₃, in a live Kaggle competition run by NVIDIA to fine-tune a 30B Nemotron model. The challenge was to teach the model to reason better — all competitors had access to the same information and were graded externally on a private test set.

AIRA₃ placed 8th out of ~4,000 teams to win Gold, outperforming human competitors who had access to the same frontier tools.

We believe this is a reliable signal that AIRA₃ can improve a targeted capability of an AI model at a level similar to human experts.

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Muse Spark 1.3 with max reasoning is now available on Muse Code and Meta Model API 👇

AI at Meta (@AIatMeta) — Fri, 04 Sep 2026 18:20:21 GMT

Muse Spark 1.3 with max reasoning is now available on Muse Code and Meta Model API 👇

Alexandr Wang@alexandr_wang

1/ we just publicly released Muse Spark 1.3 max!

we see significantly stronger coding and agentic performance on muse spark 1.3 max, so would strongly recommend trying it out even if you've already tried muse spark 1.3 high or muse spark 1.3 xhigh.

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Muse Spark 1.3 is rolling out today in Muse Code and Meta Model API at https://t.co/EMi0nXEvtz, with...

AI at Meta (@AIatMeta) — Wed, 02 Sep 2026 19:36:20 GMT

Muse Spark 1.3 is rolling out today in Muse Code and Meta Model API at dev.meta.ai, with max reasoning coming soon after we finish safety testing.

Learn more: go.meta.me/46IsHsV

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Stay tuned for more updates soon, including bigger models, Muse Spark open weights, and more. 🚀

AI at Meta (@AIatMeta) — Wed, 02 Sep 2026 19:36:20 GMT

Stay tuned for more updates soon, including bigger models, Muse Spark open weights, and more. 🚀

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We’re excited to release Muse Spark 1.3 with improved performance on agentic and coding tasks, and a...

AI at Meta (@AIatMeta) — Wed, 02 Sep 2026 19:36:19 GMT

We’re excited to release Muse Spark 1.3 with improved performance on agentic and coding tasks, and a focus on real-world usability.

Key capabilities:
→ Sustains longer-horizon work across multiple workflows in a single thread
→ More actively collaborates with users: it asks clarifying questions, flags when it's stuck, confirms before consequential actions
→ Better calibrated on its own limits instead of hallucinating outcomes
→ ~20% fewer tool calls and ~25% fewer tokens vs. Muse Spark 1.2 in internal comparisons

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Muse Voice Transcribe is available today via Meta Model API, Meta AI for Mac, and Muse Code. Learn ...

AI at Meta (@AIatMeta) — Tue, 01 Sep 2026 17:26:10 GMT

Muse Voice Transcribe is available today via Meta Model API, Meta AI for Mac, and Muse Code.

Learn more: go.meta.me/4xISnl2

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With adaptive delay, Muse Voice Transcribe achieves the pareto frontier on speed-accuracy trade-off ...

AI at Meta (@AIatMeta) — Tue, 01 Sep 2026 17:26:09 GMT

With adaptive delay, Muse Voice Transcribe achieves the pareto frontier on speed-accuracy trade-off measured by time to final transcription.

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Introducing Muse Voice Transcribe, the first real-time audio perception model from Meta Superintelli...

AI at Meta (@AIatMeta) — Tue, 01 Sep 2026 17:26:08 GMT

Introducing Muse Voice Transcribe, the first real-time audio perception model from Meta Superintelligence Labs.

Muse Voice Transcribe delivers real-time streaming ASR, diarization with 20+ speakers, and endpointing. It’s multilingual with seamless code-switching and improves accuracy with language, keyword, and context biasing.

The model ranks first on @ArtificialAnlys streaming speech-to-text and on public diarization benchmarks.

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Here are the generated artifacts of Muse Spark 1.1 and 1.2 on the Plywood Whale: https://t.co/q5dATH...

AI at Meta (@AIatMeta) — Thu, 20 Aug 2026 18:25:07 GMT

Here are the generated artifacts of Muse Spark 1.1 and 1.2 on the Plywood Whale: research.meta.ai/wild-artifact-…

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Here are the generated artifacts of Muse Spark 1.1 and 1.2 on the Cat Mesh: https://t.co/loY5g46x1V

AI at Meta (@AIatMeta) — Thu, 20 Aug 2026 18:25:06 GMT

Here are the generated artifacts of Muse Spark 1.1 and 1.2 on the Cat Mesh: research.meta.ai/wild-artifact-…

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Today we’re also previewing WildArtifactBench, an internal evaluation framework designed to assess a...

AI at Meta (@AIatMeta) — Thu, 20 Aug 2026 18:25:05 GMT

Today we’re also previewing WildArtifactBench, an internal evaluation framework designed to assess agents on complex, real-world tasks across diverse deliverable formats.

By using win rates and Elo scores from human and agentic preference judges rather than strict ground-truth rubrics, it expands task coverage across practical multimodal workflows.

We’re releasing 10 tasks from WildArtifactBench as a step forward in our ability to measure the real practical utility delivered by multimodal agents: research.meta.ai/wild-artifact-…

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Muse Spark brings spatial intelligence to robotics. A specialized variant of Muse Spark acts as the ...

AI at Meta (@AIatMeta) — Thu, 20 Aug 2026 17:06:57 GMT

Muse Spark brings spatial intelligence to robotics. A specialized variant of Muse Spark acts as the robot brain and orchestrator: it takes a user instruction, decodes tool calls, observes the results, and loops until the task is complete.

As shown in this demo, Muse Spark 1.2 can plan sub-tasks for a bimanual robot tidying a desk, distinguishing a hair brush from a makeup brush and placing the lipstick in a drawer.

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Internally, Muse Spark is deployed in several areas including media generation. For example, the mod...

AI at Meta (@AIatMeta) — Thu, 20 Aug 2026 17:06:57 GMT

Internally, Muse Spark is deployed in several areas including media generation. For example, the model works with Muse Image for agentic media generation and produces detailed captions as training data for Muse Image and Muse Video. Muse Spark is also able to translate raw text, image, and video content into signals and insights that can be used in downstream applications.

See more Muse Spark 1.2 evals and demos here: go.meta.me/multimodal

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Muse Spark 1.2 supports a broad range of multimodal tasks, from turning visuals into working code to...

AI at Meta (@AIatMeta) — Thu, 20 Aug 2026 17:06:55 GMT

Muse Spark 1.2 supports a broad range of multimodal tasks, from turning visuals into working code to translating perception into physical action. It also brings robust audio-visual understanding to enable video-heavy workflows common in real-world enterprise use.

Today, we’re sharing new evals and demos that illustrate the breadth of the model’s visual understanding and reasoning capabilities.

Let’s start with a demo that shows how Muse Spark parses multimodal observations and calls tools to guide a robot to navigate in an unstructured environment to find a rubber duck.

🧵👇

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🔗 Download Muse Glimmer on @huggingface: https://t.co/s7Lzb8MqCG 🔗 Read the technical blog: https...

AI at Meta (@AIatMeta) — Mon, 10 Aug 2026 10:13:36 GMT

🔗 Download Muse Glimmer on @huggingface:huggingface.co/meta-modelsG

🔗 Read the technical bloggo.meta.me/museglimmerbc

🔗 Find resourcedeveloper.meta.com/ai/models/muse…FwU

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Muse Glimmer can complete multi-step agentic tasks end-to-end from a single natural language prompt....

AI at Meta (@AIatMeta) — Mon, 10 Aug 2026 10:13:35 GMT

Muse Glimmer can complete multi-step agentic tasks end-to-end from a single natural language prompt.

In this demo, it autonomously discovers a local Home Assistant instance via network tool calls, queries device APIs, writes a responsive HTML/CSS/JS dashboard from scratch, and deploys a local server for verification.

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For a local agent to be practical, generation latency must be low enough to maintain workflow contin...

AI at Meta (@AIatMeta) — Mon, 10 Aug 2026 10:13:35 GMT

For a local agent to be practical, generation latency must be low enough to maintain workflow continuity.

To run Muse Glimmer on consumer hardware without degrading quality, we used quantization to shrink the language model to under 20GB and a lightweight DFlash drafter model to accelerate token generation. As a result, Muse Glimmer is fast enough for fluid conversation and real-time agent interaction, all running entirely on your device.

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Introducing Muse Glimmer, an open-weight 30B-parameter model optimized for local, always-on agent wo...

AI at Meta (@AIatMeta) — Mon, 10 Aug 2026 10:13:34 GMT

Introducing Muse Glimmer, an open-weight 30B-parameter model optimized for local, always-on agent workflows.

Muse Glimmer delivers strong performance on key agentic use cases and benchmarks compared with leading models in its size category, and is designed to run entirely on consumer hardware like a Mac or PCs with performant GPUs.

In keeping with our long tradition of sharing fundamental AI research, we’re releasing model weights under a permissive Apache 2.0 license.

🧵👇

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To understand whether we're making genuine progress on reasoning, we entered our AI models in five S...

AI at Meta (@AIatMeta) — Thu, 06 Aug 2026 15:34:03 GMT

To understand whether we're making genuine progress on reasoning, we entered our AI models in five STEM Olympiad competitions.

The results:
🏅 Asian Physics Olympiad (APhO): Perfect score, theory exam
🏅 International Physics Olympiad (IPhO): Perfect score, theory exam
🥇 International Mathematical Olympiad (IMO): Gold medal
🥇 International Chemistry Olympiad (IChO): Gold-medal-level performance
🥇 Romanian Masters of Mathematics (RMM): Gold-medal-level performance

The types of problems in the Olympiad competitions are exceptionally hard, demanding deep chains of reasoning, creative insight, and flawless argumentation. To test pure reasoning capability, we disallowed all tool use, meaning no search, no coding, and no calculator.

We have deep admiration for the contestants and committees behind these competitions, and are grateful for their support in enabling our participation.

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@sunglassesface @OpenRouter No worries, Muse Spark 1.2 is available on OpenRouter with the same glob...

AI at Meta (@AIatMeta) — Wed, 05 Aug 2026 23:01:11 GMT

@sunglassesface@OpenRouter No worries, Muse Spark 1.2 is available on OpenRouter with the same global availability as Meta Model API.

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Here’s an example of Muse Code’s multimodal visual coding capabilities. In this demo, the user input...

AI at Meta (@AIatMeta) — Wed, 05 Aug 2026 19:25:10 GMT

Here’s an example of Muse Code’s multimodal visual coding capabilities. In this demo, the user inputs a fly-through video of a home into the terminal as an mp4 file. Muse Code interprets the video and produces a visually rich website with booking capabilities.

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Muse Spark 1.2 is available today in Muse Code and in Meta Model API, with expanded global access an...

AI at Meta (@AIatMeta) — Wed, 05 Aug 2026 19:25:10 GMT

Muse Spark 1.2 is available today in Muse Code and in Meta Model API, with expanded global access and many new features on the horizon.

➡️ Learn more: go.meta.me/musecode

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Muse Spark 1.2 has improved coding capabilities compared to its predecessor. We significantly scaled...

AI at Meta (@AIatMeta) — Wed, 05 Aug 2026 19:25:09 GMT

Muse Spark 1.2 has improved coding capabilities compared to its predecessor. We significantly scaled up training compute on coding tasks while expanding training environment diversity, delivering improvements in code generation, complex debugging, and end-to-end developer workflows.

The model was co-trained with Muse Code to optimize performance when paired together, and focused on tasks like whole-repo generation, large projects, and auto-research.

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Introducing Muse Code (beta), a terminal coding agent built for long-horizon software engineering, p...

AI at Meta (@AIatMeta) — Wed, 05 Aug 2026 19:25:08 GMT

Introducing Muse Code (beta), a terminal coding agent built for long-horizon software engineering, powered by our new Muse Spark 1.2 model.

Muse Code plans, implements, and validates complex, multi-file changes across large repositories with persistent sub-agents that solve difficult problems faster, more accurately, and with less intervention.

🧵👇

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To accelerate scientific discovery and support @ENERGY’s Genesis Mission, the @BerkeleyLab-led SYNAP...

AI at Meta (@AIatMeta) — Tue, 21 Jul 2026 17:07:11 GMT

To accelerate scientific discovery and support @ENERGY’s Genesis Mission, the @BerkeleyLab-led SYNAPS-I project is using SAM 3 and DINOv3 to automate image segmentation.

By pairing DINOv3’s global semantic context and fine-grained spatial localization with SAM 3’s pixel-level boundary extraction, the researchers are able to compress 3D volume labeling from a month of manual effort to ~15 minutes.

Learn more about their work: go.meta.me/01aed3

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We heard you and are happy to announce that Muse Spark 1.1 is now available on @OpenRouter for US-ba...

AI at Meta (@AIatMeta) — Thu, 16 Jul 2026 17:17:39 GMT

We heard you and are happy to announce that Muse Spark 1.1 is now available on @OpenRouter for US-based developers. 

We look forward to seeing what the community builds.

Lorenzo Nuvoletta@nuvolore

@OpenRouter when Muse Spark 1.1?

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Get started: https://t.co/ZkRx8Swu9P

AI at Meta (@AIatMeta) — Thu, 16 Jul 2026 17:17:39 GMT

Get started: go.meta.me/e3b99d

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To demonstrate Meta AI's advanced reasoning and multimodal capabilities, we submitted a model to par...

AI at Meta (@AIatMeta) — Tue, 14 Jul 2026 21:09:57 GMT

To demonstrate Meta AI's advanced reasoning and multimodal capabilities, we submitted a model to participate in the Asian Physics Olympiad’s theoretical exam. We’re happy to share that our model achieved a perfect score of 30/30, tying with the top 3 student contestants.

We appreciate the APhO committee for letting our model participate in the competition:  apho2026.kr/en/index.html

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We gave a few leaders early access to Muse Spark 1.1, here's what they had to say:

AI at Meta (@AIatMeta) — Thu, 09 Jul 2026 19:53:11 GMT

We gave a few leaders early access to Muse Spark 1.1, here's what they had to say:

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@WorldsByMike @whylifeis4 Find the Meta Model API here: https://t.co/CyWvhTE540

AI at Meta (@AIatMeta) — Thu, 09 Jul 2026 14:31:21 GMT

@WorldsByMike@whylifeis4 Find the Meta Model API here: developer.meta.com/ai/products/me…

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Muse Spark 1.1 also excels in perception and multimodal reasoning, inspecting visual and audio input...

AI at Meta (@AIatMeta) — Thu, 09 Jul 2026 14:10:41 GMT

Muse Spark 1.1 also excels in perception and multimodal reasoning, inspecting visual and audio inputs, preserving details across long workflows, and acting on them in real execution environments. It shows particular strengths in visual-to-code generation, rich image/video captioning, and agentic computer use.

In this demo, using video shot from a smartphone, Muse Spark 1.1 extracts useful photos and reasons about the product to operate a user's browser and make a Facebook Marketplace listing on the user's behalf.

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Muse Spark 1.1 is used across Meta in coding and research workflows, scoring competitively with lead...

AI at Meta (@AIatMeta) — Thu, 09 Jul 2026 14:10:40 GMT

Muse Spark 1.1 is used across Meta in coding and research workflows, scoring competitively with leading models on Meta's internal coding benchmark.

Our researchers are now automating model development and evaluation tasks by leveraging Muse Spark 1.1 in their workflows.

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Muse Spark 1.1 is a multimodal reasoning model built for agentic tasks, with major gains in tool and...

AI at Meta (@AIatMeta) — Thu, 09 Jul 2026 14:10:38 GMT

Muse Spark 1.1 is a multimodal reasoning model built for agentic tasks, with major gains in tool and computer use, coding, and multimodal understanding.

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We’re excited to introduce Muse Spark 1.1, a significant upgrade from the first Muse Spark model we ...

AI at Meta (@AIatMeta) — Thu, 09 Jul 2026 14:10:37 GMT

We’re excited to introduce Muse Spark 1.1, a significant upgrade from the first Muse Spark model we released earlier this year.

Along with this release, we are launching a public preview of the new Meta Model API where developers can access Muse Spark 1.1.

The model is also available now in "Thinking" mode in the Meta AI app and on meta.ai.

Learn more: go.meta.me/ff8e2c

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Straight from @finkd — Muse Spark 1.1 is live.

AI at Meta (@AIatMeta) — Thu, 09 Jul 2026 14:00:55 GMT

Straight from @finkd — Muse Spark 1.1 is live.

Mark Zuckerberg@finkd

(1) Today we're releasing Muse Spark 1.1 -- a strong agentic and coding model at a very low price. It's available through our new Meta Model API and in Meta AI.

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Alongside the release of Muse Image, we’re sharing an early preview of Muse Video. It offers competi...

AI at Meta (@AIatMeta) — Tue, 07 Jul 2026 21:02:45 GMT

Alongside the release of Muse Image, we’re sharing an early preview of Muse Video. It offers competitive performance in prompt adherence, visual fidelity, and temporal consistency.

We’re investing in areas with current performance gaps, such as audio-video synchronization and physically accurate fast motion.

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AI at Meta@AIatMeta

Introducing Muse Image and Muse Video, the first media generation models developed by Meta Superintelligence Labs.

Muse Image is our most advanced image generation model yet. It follows instructions faithfully, edits with precision, composes from multiple references, and draws on Instagram for social context. It also brings agentic tool use capabilities to image generation and integrates with Muse Spark.

You can try Muse Image in the Meta AI app and web, as well as in Instagram Stories and WhatsApp – starting in limited countries with more locations on the way.

Today we’re also previewing Muse Video, which is built upon the same pretraining base as Muse Image to deliver exceptional visual fidelity with native audio support.

Learn more about both models: go.meta.me/7f4427

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Content Seal is built into the Meta AI app and https://t.co/wHkMPH7va9 — every generated image carri...

AI at Meta (@AIatMeta) — Tue, 07 Jul 2026 20:14:30 GMT

Content Seal is built into the Meta AI app and meta.ai — every generated image carries a hidden provenance signal that stays intact through cropping, compression, and resizing.

We are previewing a public identification tool to verify the presence of this watermark on images created by the Meta AI app or meta.ai: meta.ai/identification

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Muse Image demonstrates emergent self-refinement within its chain of thought, adaptively executing l...

AI at Meta (@AIatMeta) — Tue, 07 Jul 2026 20:14:29 GMT

Muse Image demonstrates emergent self-refinement within its chain of thought, adaptively executing local edits, complete re-generation, or tool use. Rather than being explicitly programmed, this behavior emerged during RL training as a strategy to optimize image quality and maximize reward.

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Muse Image thinks before it creates. Driven by reinforcement learning, the model utilizes test-time ...

AI at Meta (@AIatMeta) — Tue, 07 Jul 2026 20:14:28 GMT

Muse Image thinks before it creates. Driven by reinforcement learning, the model utilizes test-time compute to achieve predictable, log-linear Elo scaling based on the combined total of text and visual tokens.

Allocating test-time compute to this deliberate reasoning and tool execution yields significantly better scalability than standard Best-of-N sampling.

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Muse Image works as an agent rather than a direct prompt-to-image model: it invokes tools, self-refi...

AI at Meta (@AIatMeta) — Tue, 07 Jul 2026 20:14:25 GMT

Muse Image works as an agent rather than a direct prompt-to-image model: it invokes tools, self-refines, improves with scaled test-time compute, and pairs with Muse Spark for collaborative media generation.

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AI at Meta@AIatMeta

Introducing Muse Image and Muse Video, the first media generation models developed by Meta Superintelligence Labs.

Muse Image is our most advanced image generation model yet. It follows instructions faithfully, edits with precision, composes from multiple references, and draws on Instagram for social context. It also brings agentic tool use capabilities to image generation and integrates with Muse Spark.

You can try Muse Image in the Meta AI app and web, as well as in Instagram Stories and WhatsApp – starting in limited countries with more locations on the way.

Today we’re also previewing Muse Video, which is built upon the same pretraining base as Muse Image to deliver exceptional visual fidelity with native audio support.

Learn more about both models: go.meta.me/7f4427

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Introducing Muse Image and Muse Video, the first media generation models developed by Meta Superinte...

AI at Meta (@AIatMeta) — Tue, 07 Jul 2026 19:33:53 GMT

Introducing Muse Image and Muse Video, the first media generation models developed by Meta Superintelligence Labs.

Muse Image is our most advanced image generation model yet. It follows instructions faithfully, edits with precision, composes from multiple references, and draws on Instagram for social context. It also brings agentic tool use capabilities to image generation and integrates with Muse Spark.

You can try Muse Image in the Meta AI app and web, as well as in Instagram Stories and WhatsApp – starting in limited countries with more locations on the way.

Today we’re also previewing Muse Video, which is built upon the same pretraining base as Muse Image to deliver exceptional visual fidelity with native audio support.

Learn more about both models: go.meta.me/7f4427

Your browser does not support the video tag.

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@bcbl_ For clarification, Brain2Qwerty v1 was published earlier today in @NatureNeuro.

AI at Meta (@AIatMeta) — Mon, 29 Jun 2026 13:07:04 GMT

@bcbl_ For clarification, Brain2Qwerty v1 was published earlier today in @NatureNeuro.

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To help accelerate neuroscience breakthroughs, we're releasing the full training code for Brain2Qwer...

AI at Meta (@AIatMeta) — Mon, 29 Jun 2026 12:10:19 GMT

To help accelerate neuroscience breakthroughs, we're releasing the full training code for Brain2Qwerty v1 and v2, and our partner, @bcbl_, is releasing the v1 dataset.

Learn more and explore the artifacts here: go.meta.me/42ed9c

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We trained Brain2Qwerty v2 on ~22,000 sentences from 9 volunteers, each recorded for 10 hours wearin...

AI at Meta (@AIatMeta) — Mon, 29 Jun 2026 12:10:18 GMT

We trained Brain2Qwerty v2 on ~22,000 sentences from 9 volunteers, each recorded for 10 hours wearing an MEG device while typing.

By using end-to-end deep learning on raw brain signals from MEG devices and fine-tuning LLMs, the system effectively bridges the gap between noisy neural data and coherent language.

The results are promising:
- Avg word accuracy of 61% across participants
- 78% word accuracy and 50%+ of sentences decoded with ≤ 1 word error for the top-performing participant
- Performance scales log-linearly with data volume

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