📢 The test set for this year's Open Catalyst Challenge is now available! 🚀 Download links are waiting for you on the challenge website: opencatalystproject.org/challenge.html. Submissions are open until Oct. 13th. Best of luck to all participants! We can't wait to see your innovations! 👏

🎉 Excited to introduce Joint Multi-domain Pre-training (JMP) - our new pre-training method leveraging diverse chemical data at scale. JMP achieves SOTA performance on 34/40 evaluated tasks from QM9, rMD17, MD22, SPICE, MatBench, and QMOF. (1/5) arxiv.org/abs/2310.16802

Today, Meta & Georgia Tech researchers are releasing a new dataset + associated AI models to help accelerate research on Direct Air Capture — a key technology needed to combat climate change. Paper ➡️ bit.ly/46X0kWs Models & dataset ➡️ bit.ly/47gEKfy

Announcing the Open Catalyst Intro video series! Want to learn more about how we can help mitigate climate change through advances in AI and chemistry? We’re creating a video series to help AI researchers get up to speed in this exciting research area! youtube.com/playlist?list=…

Today we’re releasing Code Llama 70B: a new, more performant version of our LLM for code generation — available under the same license as previous Code Llama models. Download the models ➡️ bit.ly/3Oil6bQ • CodeLlama-70B • CodeLlama-70B-Python • CodeLlama-70B-Instruct

Check out the latest installment in the Open Catalyst Intro Series! youtube.com/watch?v=HpZDHZ…

Newly published today in ACS Central Science — Meta and Georgia Tech researchers released a dataset + SOTA AI models to help accelerate research on Direct Air Capture — a key technology to combat climate change ➡️ go.fb.me/eojy3k

Proud of this work coming out of a collaboration between FAIR researchers & Georgia Tech that was just published in ACS Central Science! The dataset & AI models that we released together could help meaningfully accelerate research combating climate change. open-dac.github.io

I’m excited to announce our latest paper, introducing a family of early-fusion token-in token-out (gpt4o….), models capable of interleaved text and image understanding and generation. arxiv.org/abs/2405.09818

🚀We're excited to emerge from stealth and announce our $30M Seed financing round. A huge thank you to our incredible investor group including Hoxton Ventures, Basis Set, Lightspeed, Northzone, LocalGlobe, Touring Capital, Giant Ventures, FJ Labs, Zero Prime VC & Tiferes

Today is a good day for open science. As part of our continued commitment to the growth and development of an open ecosystem, today at Meta FAIR we’re announcing four new publicly available AI models and additional research artifacts to inspire innovation in the community and

Last week we released Meta Chameleon: a new mixed-modal research model from Meta FAIR. Get the models ➡️ go.fb.me/4m87kk The 7B & 34B safety tuned models we’ve released can take any combination of text and images as input and produce text outputs using a new early

ESMFold used in finding some 70k new RNA viruses :) nature.com/articles/d4158…

Introducing Meta’s Open Materials 2024 (OMat24) Dataset and Models! All under permissive open licenses for commercial and non-commercial use! Paper: arxiv.org/abs/2410.12771 Dataset: huggingface.co/datasets/fairc… Models: huggingface.co/fairchem/OMAT24 🧵1/x

Want to do research in code generation with LLMs and wonky deep learning from the 90s? We're recruiting one Master student (M2) intern for 2025 at FAIR Paris in my team metacareers.com/jobs/106871446…

New open source release — Meta Open Materials 2024: a new open source model and dataset from Meta FAIR to facilitate inorganic materials discovery. The Open Materials 2024 models deliver results putting them at the top of the MatBench-Discovery leaderboard. They use the

Excited to unveil OCx24, a two-year effort with University of Toronto and @VSParticle! We've synthesized and tested in the lab hundreds of metal alloys for catalysis. With 685 million AI-accelerated simulations, we analyzed 20,000 materials to try and bridge simulation and reality. Paper:

Excited to share our latest releases to the FAIR Chemistry’s family of open datasets and models: OMol25 and UMA! AI at Meta FAIR Chemistry OMol25: huggingface.co/facebook/OMol25 UMA: huggingface.co/facebook/UMA Blog: ai.meta.com/blog/meta-fair… Demo: huggingface.co/spaces/faceboo…

We're starting to see more and more AI for chemistry and biology which I'm super excited about given the potential for good! AI at Meta just released OMol25 on Hugging Face, a dataset of 𝟭𝟬𝟬𝗠+ 𝗺𝗼𝗹𝗲𝗰𝘂𝗹𝗮𝗿 𝗰𝗼𝗻𝗳𝗼𝗿𝗺𝗲𝗿𝘀 spanning 83 elements and diverse chemical

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