We’re thankful for the incredible response to Llama 2 and early uses + development already emerging in the community. With 150K+ download requests in just the first week, we can't wait to see how you build with these models. More in this note
@aiatmeta
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Meta Publishes Llama 2 Technical Paper for Community Development
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To better enable the community to build on our work — and contribute to the responsible development of LLMs — we've published further details about the architecture, training compute, approach to fine-tuning & more for Llama 2 in a new paper. Full paper https://
bit.ly/44JAELQ -
Low-cost Catalyst Materials for Renewable Energy Discovery
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Low cost catalyst materials are an important means towards a renewable energy future. By making this demo available to the public, we hope to increase the pace of material discovery for low-cost catalyst materials and showcase the emerging generalizability of these models. pic.twitter.com/6TBscu8hl5
— AI at Meta (@AIatMeta) 27 juillet 2023Low cost catalyst materials are an important means towards a renewable energy future. By making this demo available to the public, we hope to increase the pace of material discovery for low-cost catalyst materials and showcase the emerging generalizability of these models.
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AI at Atomic Level Accelerates Scientific Discovery
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Our ability to utilize AI to understand the world at the atomic level opens up a range of new possibilities, and opportunities to address some of the most pressing challenges in science. We're excited to help accelerate this field of work with the @OpenCatalyst Project.
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Open Catalyst Demo: 100M Surface-Adsorbate Combinations Analysis
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The Open Catalyst demo supports adsorption energy calculations for 11,427 catalyst materials and 86 adsorbates, which amounts to ~100M catalyst surface-adsorbate combinations — a scale impossible to explore without machine learning.
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Open Catalyst Demo Released for Accelerated Material Science Research
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Today we're releasing the Open Catalyst Demo to the public — this new service will allow researchers to accelerate work in material sciences by enabling them to simulate the reactivity of catalyst materials ~1000x faster than existing computational methods using AI.
— AI at Meta (@AIatMeta) 27 juillet 2023
Demo ⬇️Today we're releasing the Open Catalyst Demo to the public — this new service will allow researchers to accelerate work in material sciences by enabling them to simulate the reactivity of catalyst materials ~1000x faster than existing computational methods using AI. Demo
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Meta AI Research Paper Wins ICML 2023 Outstanding Paper Award
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We’re honored to share that Learning-Rate-Free Learning by D-Adaptation, a paper by Meta AI research scientist @aaron_defazio & @konstmish was selected as an #ICML2023 Outstanding Paper! More details and a link to the paper
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ICML 2023 Papers and Team Workshop Connections
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Bonus: Want to see more of our ICML papers? Or where you can connect with our team at workshops if you're at the conference? More info on our #ICML2023 page https://
bit.ly/452XCgZ 7/7 -
Hiera: Hierarchical Vision Transformer without Bells-and-Whistles
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Hiera: A Hierarchical Vision Transformer without the Bells-and-Whistles https://
bit.ly/3OrVBW3 6/7 -
Hyperbolic Image-Text Representations Research
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Hyperbolic Image-Text Representations https://
bit.ly/3YlLC8h 5/7