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Meta Superintelligence Labs has launched Muse Spark, a native multimodal reasoning model that scores 52 on the Artificial Analysis Intelligence Index, placing it in the top 5 frontier models. This marks Meta's first frontier-class model and its first AI system without open weights, representing a strategic shift from its open-source Llama strategy. The model achieves comparable efficiency to Gemini 3.1 Pro while matching Llama 4 Maverick capabilities with over an order of magnitude less compute.

Meta Superintelligence Labs has launched Muse Spark, its first model since Mark Zuckerberg restructured the company's AI division. The multimodal model now powers Meta AI's app and website in the US, with rollout planned for WhatsApp, Instagram, Facebook, Messenger, and Meta's smart glasses in coming weeks.

Meta announced Muse Spark, its first major large language model since hiring Scale AI's Alexandr Wang nine months ago for a $14.3 billion deal. The proprietary model emphasizes efficiency and multimodal reasoning over top-tier performance, marking a strategic shift from Meta's previous open-source Llama approach. Muse Spark will power Meta's AI assistant across Facebook, Instagram, WhatsApp, Messenger, and Ray-Ban glasses starting in coming weeks.

Meta has released SAM 3.1, an update to its Segment Anything Model that adds Object Multiplex, a shared-memory approach for joint multi-object tracking. The new version achieves approximately 7x faster inference when tracking 128 objects on a single H100 GPU while improving video object segmentation (VOS) performance on 6 out of 7 benchmarks.

Meta's FAIR lab released TRIBE v2, an AI model that predicts human brain activity from images, audio, and text. Trained on over 1,000 hours of fMRI data from 720 subjects, the model maps predictions to 70,000 voxels and often matches group-average brain responses more accurately than individual brain scans.

Meta's recently acquired AI startup Manus launched a desktop application enabling its AI agent to directly access local files, tools, and applications on personal computers through a 'My Computer' feature. Previously cloud-only, the move positions Manus to compete with OpenClaw, the open-source AI agent that sparked recent industry momentum. Unlike OpenClaw's free, MIT-licensed offering, Manus operates as a paid subscription service.

Meta has acquired Moltbook, a social network designed exclusively for AI agents, and hired its founders Matt Schlicht and Ben Parr to work in Meta's Superintelligence Labs run by former Scale AI CEO Alexandr Wang. The acquisition gives Meta access to Moltbook's technology for verifying agent identities and coordinating complex tasks between AI bots. The move signals Meta's intent to integrate agentic AI capabilities into its platforms, though specific plans remain undisclosed.

Meta has acquired Moltbook, a social network designed for AI agents, bringing founders Matt Schlicht and Ben Parr into Meta Superintelligence Labs under former Scale AI CEO Alexandr Wang. The move positions Meta alongside OpenAI's OpenClaw in acquiring AI agent platforms.

Meta has unveiled four generations of custom-designed AI chips focused on inference workloads, aiming to reduce inference costs across its platforms serving billions of users. The move represents a significant step toward reducing Meta's dependence on GPU manufacturers like Nvidia and AMD.

Meta has developed four new custom AI chips called MTIA (Meta Training and Inference Accelerator) processors designed to power its AI models and recommendation systems. The move represents the company's ongoing effort to reduce dependence on Nvidia's expensive processors while managing massive compute requirements.

Meta has acquired Moltbook, a Reddit-like platform where AI agents autonomously make and comment on posts. The Moltbook team, founded by Matt Schlict and Ben Parr earlier this year, will join Meta Superintelligence Labs. The platform runs on OpenClaw, an open-source AI assistant formerly called Moltbot.

Meta has acquired Moltbook, a platform built as a Reddit-style community space specifically for AI agents. The acquisition signals Meta's expanding focus on infrastructure for agent-to-agent interaction and collaboration.

Meta has committed to paying News Corp up to $50 million annually in a multi-year agreement for AI training data and content licensing. The deal represents Meta's continued strategy of securing high-quality publishing content for its AI models. The arrangement raises questions about the sustainability of individual content licensing deals versus industry-wide data standards.

Meta has signed a multi-billion dollar deal to rent Google's TPU (Tensor Processing Unit) chips for training its AI models, marking a significant shift away from Nvidia's dominance in AI infrastructure. The arrangement provides Meta with alternative compute capacity while signaling growing competition in the specialized AI chip market.