Starting today, open source is leading the way. Introducing Llama 3.1: Our most capable models yet. Today we’re releasing a collection of new models including our long awaited 405B. Llama 3.1 delivers stronger reasoning, a larger 128K context window & improved support for 8 languages including English — among other improvements. Details in the full announcement ➡️ https://go.fb.me/hvuqhb Download the models ➡️ https://go.fb.me/11ffl7 We evaluated performance across 150+ benchmark datasets across a range of languages — in addition to extensive human evaluations in real-world scenarios. Trained on >16K NVIDIA H100 GPUs, Llama 3.1 405B is the industry leading open source foundation model and delivers state-of-the-art capabilities that rival the best closed source models in general knowledge, steerability, math, tool use and multilingual translation. We’ve also updated our license to allow developers to use the outputs from Llama models — including the 405B — to improve other models for the first time. We’re excited about how synthetic data generation and model distillation workflows with Llama will help to advance the state of AI. As Mark Zuckerberg shared this morning, we have a strong belief that open source will ensure that more people around the world have access to the benefits and opportunities of AI and that’s why we continue to take steps on the path for open source AI to become the industry standard. With these releases we’re setting the stage for unprecedented new opportunities and we can’t wait to see the innovation our newest Llama models will unlock across all levels of the AI community.
AI at Meta
Research Services
Menlo Park, California 861,461 followers
Together with the AI community, we’re pushing boundaries through open science to create a more connected world.
About us
Through open science and collaboration with the AI community, we are pushing the boundaries of artificial intelligence to create a more connected world. We can’t advance the progress of AI alone, so we actively engage with the AI research and academic communities. Our goal is to advance AI in Infrastructure, Natural Language Processing, Generative AI, Vision, Human-Computer Interaction and many other areas of AI enable the community to build safe and responsible solutions to address some of the world’s greatest challenges.
- Website
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https://ai.meta.com/
External link for AI at Meta
- Industry
- Research Services
- Company size
- 10,001+ employees
- Headquarters
- Menlo Park, California
- Specialties
- research, engineering, development, software development, artificial intelligence, machine learning, machine intelligence, deep learning, computer vision, engineering, computer vision, speech recognition, and natural language processing
Updates
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We're at #INTERSPEECH2024 — if you're on the ground in Greece this week, stop by our booth to explore SeamlessExpressive, MAGNeT, EMG and more with our research teams! 🔗 Following the conference from your feed? Here are links to five papers we're presenting to add to your reading list. 1. Learning Fine-Grained Controllability on Speech Generation via Efficient Fine-Tuning: https://go.fb.me/httkop 2. Navigating the Mine Field of MT Beam Search in Cascaded Streaming Speech Translation: https://go.fb.me/3v42k5 3. Configurable Field of View Speech Enhancement with Low Compute and Low Distortion for AR Glasses: https://go.fb.me/wdb9gt 4. Towards measuring fairness in speech recognition: https://go.fb.me/y1k4kw 5. MSRS: Training Multimodal Speech Recognition Models from Scratch with Sparse Mask Optimization: https://go.fb.me/0dxi3j
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We're still accepting proposals for our LLM Evaluations Grant until this Friday, September 6th — we encourage submissions that utilize evaluations in the areas of complex reasoning, emotional & social intelligence and agentic behavior. Selected recipients will get $200K in funding to pursue further innovation in this important area of work. We're accepting proposals through September 6th and you can find the full details here ➡️ https://go.fb.me/u1xjkk
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Segment Anything Model 2 (SAM 2) is a foundation model from Meta FAIR for promptable visual segmentation in images and videos. Available now for developers, creators, hobbyists and more to build on for free, open source under an Apache 2.0 license. Try the demo ➡️ https://go.fb.me/4fqyq4
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Open source AI is the way forward and today we're sharing a snapshot of how that's going with the adoption and use of Llama models. Read the full update here ➡️ https://go.fb.me/mfc5ki 🦙 Highlights • Llama is approaching 350M downloads on Hugging Face. • Our largest cloud service providers have seen Llama token usage more than double since May. • Llama models are being adopted across the industry with great examples from Accenture, AT&T, DoorDash, Goldman Sachs, Infosys, KPMG, Niantic, Inc., Nomura, Shopify, Spotify and Zoom as just a handful of strong examples. Open source AI is how we ensure that the benefits of AI extend to everyone, and Llama is leading the way.
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AI at Meta reposted this
The deadline is rapidly approaching.. If you'd like to be considered for this round of LLM Eval Grants, please submit your proposals ASAP!! 👉 https://lnkd.in/gyGVKQY2
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New research from Meta FAIR: Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model. This recipe combines next token prediction with diffusion to train a single transformer over mixed-modality sequences. Our experiments show that Transfusion scales significantly better than traditional approaches and demonstrate that scaling to 7B parameters and 2T multi-modal tokens produces a model that is on par with similar scale language and diffusion models. More details in the full research paper ➡️ https://go.fb.me/4vnybn
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Announced today, NVIDIA NIM Agent Blueprints include everything enterprises need to build and deploy custom apps using Llama 3.1 405B. • Sample applications • Reference code • Customization documentation • A Helm chart for deployment More NIM Agent Blueprints are on the way covering use cases like content generation, software engineering, retail shopping advising and more.
📣 Announcing NVIDIA NIM Agent Blueprints, reference applications for every enterprise to make their own #AI. ➡️ https://nvda.ws/3z1HTUO These new NIM Agent Blueprints equip millions of enterprise developers with reference applications for building and deploying generative AI use cases such as digital humans, multimodal PDF data extraction, and virtual screening.
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Announced this morning and verified by Artificial Analysis, Cerebras Systems Inference is capable of serving Llama 3.1 70B at 450 tokens/sec and Llama 3.1 8B at 1,850 tokens/sec! This order of magnitude increase in inference speed for Llama 3.1 could unlock all new types of use cases for the developer community and enterprises.
Meet Cerebras Inference – the fastest inference for generative AI! 🏎️ Speed: 1,800 tokens/sec for Llama 3.1-8B and 450 tokens/sec for Llama 3.1-70B, 20x faster than NVIDIA GPU-based hyperscale clouds. 💸 Price: Cerebras Inference offers the industry’s best price-performance at 10c per million tokens for Llama 3.1-8B and 60c per million tokens for Llama-3.1 70B. 🎯 Accuracy: Cerebras Inference uses native 16-bit weights for all models, ensuring the highest accuracy responses. 🔓 Access: Cerebras Inference is open to everyone today via chat and API access. All powered by our third-generation Wafer Scale Engine (WSE-3). Try it now 👉 https://lnkd.in/gEJJ2pfY Press Release: https://lnkd.in/gtF5fxHt Blog: https://lnkd.in/gZ46q4cD
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As part of the release of Llama 3.1, we also released new trust and safety artifacts including CyberSecEval 3. We've published a new research paper on this work to continue the conversation with researchers and developers on empirically measuring LLM cybersecurity risks and capabilities. CyberSecEval 3 research paper ➡️ https://go.fb.me/yv32a9
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