Wrapping up the year and coinciding with #NeurIPS2024, today at Meta FAIR we’re releasing a collection of nine new open source AI research artifacts across our work in developing agents, robustness & safety and new architectures. More in the video from @jpineau1
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@aiatmeta
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Meta FAIR Releases Nine Open Source AI Research Artifacts
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SPDL: Framework-Agnostic Fast AI Model Training with Multi-Threading
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Introducing SPDL: Faster AI model training with thread-based data loading. This framework-agnostic data loading solution utilizes multi-threading to achieve high-throughput in a regulator Python interpreter. More details https://
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Llama 3.3 Community Launch Excitement Announced
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Excited for the community to get up and running with Llama 3.3!
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Llama 3.3: Enhanced Alignment and Cost-Effective Local Inference
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Improvements in Llama 3.3 were driven by a new alignment process and progress in online RL techniques. This model delivers similar performance to Llama 3.1 405B with cost effective inference that’s feasible to run locally on common developer workstations.
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Llama 3.3 Now Available from Meta and Hugging Face
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Llama 3.3 is available now from Meta and on @huggingface — and will be available for deployment soon through our broad ecosystem of partner platforms. Model card https://
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Download from Meta https://
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Meta Releases Llama 3.3: Open Source Model for Efficient Text Generation
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As we continue to explore new post-training techniques, today we're releasing Llama 3.3 — a new open source model that delivers leading performance and quality across text-based use cases such as synthetic data generation at a fraction of the inference cost.
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Meta announces largest AI datacenter in Louisiana with LED partnership
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Today in partnership with @LEDLouisiana
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Meta Sparsh and Recent Robotics AI Research Announcement
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You can find more on Meta Sparsh, and more of our recently announced robotics AI research in this post ➡️ https://t.co/XHL9YzxiU1 pic.twitter.com/etArvACvVz
— AI at Meta (@AIatMeta) 27 novembre 2024You can find more on Meta Sparsh, and more of our recently announced robotics AI research in this post https://
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Meta Sparsh: General-Purpose Vision-Based Tactile Sensing Encoder
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Meta Sparsh is the first general-purpose encoder for vision-based tactile sensing that works across many tactile sensors + many tasks. The family of models was pre-trained on a large dataset of 460K+ tactile images using SSL. To foster new research, we've released code, a
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IBM watsonx Studio Enables Developers to Build AI Models with Llama
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IBM watsonx provides a studio for AI builders worldwide to train, validate, tune & deploy AI models. The platfrorm is enabling developers from the financial industry to sports scouting to build impressive and impactful things with Llama https://
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