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April 29, see you at the first-ever LlamaCon. 🦙 https://t.co/pVpqNEgjKG
— AI at Meta (@AIatMeta) 18 février 2025
& we'll see you again later this year at Meta Connect, September 17-18. pic.twitter.com/vMRe25yOb1
April 29, see you at the first-ever LlamaCon. https://
go.fb.me/LlamaCon & we'll see you again later this year at Meta Connect, September 17-18.
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Meta FAIR researchers, in collaboration with @bcbl_ are sharing two breakthroughs that show how AI can help advance our understanding of human intelligence.
— AI at Meta (@AIatMeta) 14 février 2025
1️⃣ Research that successfully decodes the production of sentences from non-invasive brain recordings.
2️⃣ A study toward… pic.twitter.com/gP58atVyVE
Meta FAIR researchers, in collaboration with @bcbl_ are sharing two breakthroughs that show how AI can help advance our understanding of human intelligence. Research that successfully decodes the production of sentences from non-invasive brain recordings. A study toward
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We're excited to share these breakthroughs with the neuroscience community and hope that it will help to inspire and unlock new research in this important space. More details on this work and access to the research papers https://
go.fb.me/9dx9nz
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Our Automated Compliance Hardening (ACH) tool hardens platforms against regressions with LLM-based test generation. More on how this works and why it matters at Meta https://
go.fb.me/jyaab2
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Starting today, SAM 2.1 is available in #AmazonSageMaker JumpStart!
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Audiobox Aesthetics has already been used to enhance our work on Meta Movie Gen and we’re excited about how this research will be able to support the development of more sophisticated generative audio models. More details in this post
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New open source release from Meta FAIR: Audiobox Aesthetics was trained on 562 hours of audio aesthetic data annotated by professional raters across four dimensions to create a model that enables the automatic evaluation of aesthetics for speech, music and sound.
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More on our newest releases and impact of the open source work developed by Meta FAIR https://
go.fb.me/l9c28m
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Meta PARTNR is a research framework supporting seamless human-robot collaboration. Building on our research with Habitat, we’re open sourcing a large-scale benchmark, dataset and large planning model that we hope will enable the community to effectively train social robots.
