We’re thrilled to see our advanced ML models and EMG hardware — that transform neural signals controlling muscles at the wrist into commands that seamlessly drive computer interactions — appearing in the latest edition of @Nature. Read the story: Find more details on this work and the models on @github:

🚨 New open-source drop: The AI Alliance is now supporting Llama Stack, a modular AI application framework developed by Meta. Built for portability, developer choice, and real-world deployment. Details ⬇️ 🔗

Meta FAIR recently released the Seamless Interaction Dataset, the largest known high-quality video dataset of its kind, with: 4,000+ diverse participants 4,000+ hours of footage 65k+ interactions 5,000+ annotated samples This dataset of full-body, in-person, face-to-face interaction videos represents a crucial stepping stone to understanding and modeling how people communicate and behave when they’re together—advancing AI's ability to generate more natural conversations and human-like gestures. Download the dataset on @huggingface: Learn more about the dataset:

This week we shared an open source AI tool that will help accelerate the discovery of high-performance, low-carbon concrete. See the full story in the thread below. You can also find research artifacts for this project here: 1️⃣ Technical report with details of the model and optimization algorithm: 2️⃣ Open source SustainableConcrete repository with the associated data and code

Today Mark announced Meta's major AI compute investment. See his post:

🚀New from Meta FAIR: today we’re introducing Seamless Interaction, a research project dedicated to modeling interpersonal dynamics. The project features a family of audiovisual behavioral models, developed in collaboration with Meta’s Codec Avatars lab + Core AI lab, that render speech between two individuals into diverse, expressive full-body gestures and active listening behaviors, allowing the creation of fully embodied avatars in 2D and 3D. These models have potential to create more natural, interactive virtual agents that can engage in human-like social interactions across a variety of settings. Learn more:

🚀New from Meta FAIR: today we’re introducing Seamless Interaction, a research project dedicated to modeling interpersonal dynamics. The project features a family of audiovisual behavioral models, developed in collaboration with Meta’s Codec Avatars lab + Core AI lab, that render speech between two individuals into diverse, expressive full-body gestures and active listening behaviors, allowing the creation of fully embodied avatars in 2D and 3D. These models have potential to create more natural, interactive virtual agents that can engage in human-like social interactions across a variety of settings. Learn more:

🚀New from Meta FAIR: today we’re introducing Seamless Interaction, a research project dedicated to modeling interpersonal dynamics. The project features a family of audiovisual behavioral models, developed in collaboration with Meta’s Codec Avatars lab + Core AI lab, that render speech between two individuals into diverse, expressive full-body gestures and active listening behaviors, allowing the creation of fully embodied avatars in 2D and 3D. These models have potential to create more natural, interactive virtual agents that can engage in human-like social interactions across a variety of settings. Learn more:

Tired of manual prompt tweaking? Watch the latest Llama tutorial on how to optimize your existing GPT or other LLM prompts for Llama with `llama-prompt-ops`, the open-source Python library! In this video, Partner Engineer Justin Lee demonstrates installation, project setup, migrating your first prompt, and analyzing performance gains. Watch now to discover: ✨ Why systematic prompt optimization is crucial for migrating from GPT to Llama. 💻 A live code walkthrough of `llama-prompt-ops` in action for a customer service classification task. Watch the full tutorial here:

Take your AI development skills to the next level with our latest course on , "Building with Llama 4", taught by @AndrewYNg and Amit Sangani, Director of Partner Engineering for Meta's AI team. In this comprehensive course, you'll learn how to harness the power of Llama 4, which enables deployment easier than before and achieves more advanced multi-modal understanding by prompting over multiple images. You'll discover how to: - Build applications that reason over visual content, detect objects, and answer image grounding questions with precision - Understand the Llama 4 prompt format especially the new image related tokens - Use long context to process entire books and research papers without needing to chunk the data - Optimize your prompts with the Llama prompt optimization tool - Create high-quality training data with the Llama Synthetic Data Kit With hands-on experience using Llama 4 through Meta's official API and other inference providers, you'll be able to build more powerful applications. Start learning now at and unlock the full potential of Llama 4!