AI at Meta (@aiatmeta) 's Twitter Profile
AI at Meta

@aiatmeta

Together with the AI community, we are pushing the boundaries of what’s possible through open science to create a more connected world.

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linkhttps://ai.meta.com calendar_today29-08-2018 16:45:58

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Meet Solo Tech, one of the 10 international recipients of the second Llama Impact Grants. Solo Tech uses Llama to offer offline, multilingual AI support for underserved rural communities with limited internet access. This grant will help them to equip 50 rural centers with AI

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Curious about the tech behind Edits? Our latest blog post explores how Meta Segment Anything Model (SAM) 2.1 is enabling the Cutouts feature in the new Edits app. Learn more: ai.meta.com/blog/instagram…

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We’re excited to announce the 10 international recipients of the second Llama Impact Grants and celebrate how they’re using open source AI to drive drive innovation and economic growth. about.fb.com/news/2025/04/l…

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Introducing Meta Perception Encoder: a vision encoder setting new standards in image & video tasks. It excels in zero-shot classification & retrieval, surpassing existing models. Learn more about Meta Perception Encoder, read the research paper, and download the code and dataset

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Introducing Meta Perception Language Model (PLM): an open & reproducible vision-language model tackling challenging visual tasks. Learn more about how PLM can help the open source community build more capable computer vision systems. Read the research paper, and download the

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Introducing Meta Locate 3D: a model for accurate object localization in 3D environments. Learn how Meta Locate 3D can help robots accurately understand their surroundings and interact more naturally with humans. You can download the model and dataset, read our research paper,

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Meta and NVIDIA have teamed up to supercharge vector search on GPUs by integrating NVIDIA cuVS into Faiss v1.10, Meta’s open-source library for similarity search. This collaboration brings groundbreaking performance improvements: 🔹 IVF indexing: NVIDIA cuVS boosts build times

Meta and NVIDIA have teamed up to supercharge vector search on GPUs by integrating NVIDIA cuVS into Faiss v1.10, Meta’s open-source library for similarity search. This collaboration brings groundbreaking performance improvements:

🔹 IVF indexing: NVIDIA cuVS boosts build times
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We’re releasing model weights for our 8B- parameter Dynamic Byte Latent Transformer, an alternative to traditional tokenization methods with the potential to redefine the standards for language model efficiency and reliability. Learn more about how Dynamic Byte Latent

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Introducing Collaborative Reasoner: a framework to improve collaborative reasoning in language models. Collaborative Reasoner paves the way for developing social agents that can partner with humans and other agents. Read the research paper and download the code.

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Following the success of its ICML 2024 tutorial, we're now releasing Part 4 of Physics of Language Models—a research effort from FAIR at Meta to uncover universal laws of AI through controlled, scientific experimentation. In Part 4, we challenge today's architecture design

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CATransformers is a carbon-driven neural architecture and system hardware co-design framework. Using CATransformers, we discover greener CLIP models that achieve an average of 9.1% reduction potential in total lifecycle carbon emissions while maintaining accuracy (or increasing

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Announcing the newest releases from Meta FAIR. We’re releasing new groundbreaking models, benchmarks, and datasets that will transform the way researchers approach molecular property prediction, language processing, and neuroscience. 1️⃣ Open Molecules 2025 (OMol25): A dataset

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We’ve released Open Molecules 2025 (OMol25), a new Density Functional Theory (DFT) dataset for molecular chemistry, and Meta's Universal Model for Atoms (UMA), a machine learning interatomic potential. These tools will accelerate molecular and materials discovery, unlocking new

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Exciting news coming out of Microsoft Build: Coming soon, the Llama herd of models will be direct first-party offerings in Azure AI Foundry, hosted and sold directly by Microsoft—with all the SLAs Azure customers expect from any Microsoft product. We’re thrilled to make it even

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Introducing Adjoint Sampling, a new learning algorithm that trains generative models based on scalar rewards. Based on theoretical foundations developed by FAIR, Adjoint Sampling leads to a highly scalable practical algorithm, and can become the foundation for further research

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🚀Applications are open for the Llama Startup Program!🚀 We're thrilled to announce the Llama Startup Program, a new initiative designed to empower early-stage startups to innovate and build generative AI applications with Llama. Why Join the Llama Startup Program? ☑️Cloud

🚀Applications are open for the Llama Startup Program!🚀

We're thrilled to announce the Llama Startup Program, a new initiative designed to empower early-stage startups to innovate and build generative AI applications with Llama.

Why Join the Llama Startup Program?
☑️Cloud
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Meta FAIR and Rothschild Foundation Hospital present a groundbreaking study mapping how language representations emerge in the brain, revealing striking parallels with LLMs. This research offers unprecedented insights into the neural development of language, showing how AI