Announced today, @NVIDIA NIM Agent Blueprints include sample applications, reference code, customization documentation and a Helm chart for deployment — everything enterprises need to build and deploy custom apps using Llama 3.1 405B.
@aiatmeta
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Cerebras Inference Achieves Record Throughput for Llama 3.1 Models
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Verified by @ArtificialAnlys, @CerebrasSystems Inference is capable of serving Llama 3.1 70B at 450 tokens/sec and Llama 3.1 8B at 1,850 tokens/sec! https://t.co/hCb9MmSvOo
— AI at Meta (@AIatMeta) 27 août 2024Verified by @ArtificialAnlys
, @cerebras Inference is capable of serving Llama 3.1 70B at 450 tokens/sec and Llama 3.1 8B at 1,850 tokens/sec! -
Meta Releases Llama 3.1 with CyberSecEval 3 Trust Safety Research
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As part of the release of Llama 3.1, we also released new trust & safety research including CyberSecEval 3. We've published our research on this work to continue the conversation on empirically measuring LLM cybersecurity risks & capabilities. Paper https://
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Meta Releases SAM 2 Open Source Visual Segmentation Model
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Segment Anything Model 2 (SAM 2) is a foundation model from Meta FAIR for promptable visual segmentation in images & videos.
— AI at Meta (@AIatMeta) 23 août 2024
Available now for anyone to build on for free, open source under an Apache license.
Try the demo ➡️ https://t.co/sTBToIR43x pic.twitter.com/iO1TlCej7xSegment Anything Model 2 (SAM 2) is a foundation model from Meta FAIR for promptable visual segmentation in images & videos. Available now for anyone to build on for free, open source under an Apache license. Try the demo https://
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New Free Course on Improving LLM Applications Accuracy
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New course on @DeepLearningAI
: Improving Accuracy of LLM Applications https://
go.fb.me/zfwvd8 Created in collaboration with DL, Meta & @LaminiAI
, this free course covers topics like evaluation frameworks, instruction & memory fine-tuning, LoRA + training data generation. -
Spotify and Meta Support Clear AI Regulation for Innovation
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"Though Spotify and Meta use AI in different ways, we agree that thoughtful, clear and consistent regulation can foster competition and innovation while also protecting people and giving them access to new technologies that empower them."
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UniBench: Comprehensive Tools for VLM Model Evaluation
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We've published the comprehensive set of tools and scripts for evaluating VLM models and benchmarks in the UniBench repo
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Meta FAIR Introduces UniBench: Unified VLM Benchmark Suite
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New research from Meta FAIR: UniBench is a unified implementation of 50+ VLM benchmarks spanning a comprehensive range of carefully categorized capabilities from object recognition to spatial awareness, counting and much more. Research paper https://
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Meta AI Launches Personalized Image Generation Without Fine-Tuning
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Research paper from GenAI at Meta: Imagine yourself: Tuning-Free Personalized Image Generation. Research paper https://
go.fb.me/wre8f0 Want to try it? The feature is available now as a beta in Meta AI for users in the US. -
Meta accelerates machine learning developer productivity
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A closer look at how we're enabling greater developer velocity for machine learning work at Meta.