AI at Meta

Introducing Meta Llama 3: the next generation of our state-of-the-art open source large language model — and the most capable openly available LLM to date. These next-generation models demonstrate SOTA performance on a wide range of industry benchmarks and offer new capabilities such as improved reasoning. Details in the full announcement ➡️ https://go.fb.me/a24u0h Download the models ➡️ https://go.fb.me/q8yhmh Experience Llama 3 with Meta AI ➡️ https://meta.ai Llama 3 8B & 70B deliver a major leap over Llama 2 and establish a new SOTA for models of their sizes. While we’re releasing these first two models today, we’re working to release even more for Llama 3 including multiple models with capabilities such as multimodality, multilinguality, longer context windows and more. Our largest models are over 400B parameters and while they’re still in active development, we’re very excited about how they’re trending. Across the stack, we want to kickstart the next wave of innovation in AI. We believe these are the best open source models of their class, period — we can’t wait to see what you build and look forward to your feedback.

Are you building something cool with Meta Llama models? Already launched something that's having an impact in your community? We'd love to hear about it! Share your Llama story ➡️ https://go.fb.me/s8ojyi

Together with Cerebral Valley, we recently hosted the first-ever Meta Llama 3 Hackathon. After receiving over 1,200 applications, we brought together 350+ attendees who built some incredible projects in just 24 hours. See the full recap and top projects here ➡️ https://go.fb.me/6dg1ib

👨🍳 Recipes for open source / local agents with Llama 3 Since the release of Llama 3, we've seen high interest in building agents that run reliably and / or locally (e.g., on your laptop). We've partnered with Meta to release several new recipes for Llama 3 agents using LangGraph. 1/ We show how to build LangGraph tool-calling agents, using Groq, which supports fast inference and tool-calling. 2/ We show how to RAG agents using LangGraph and Groq, capable of complex self-corrective control flow. 3/ We show how to take the RAG agent and make it run locally using Nomic AI embeddsm, and Ollama. ➡️ Code: https://lnkd.in/gu_3_vuN 📽️ Video: https://lnkd.in/gEgArrK9

The flexibility and open ecosystem around Meta Llama are enabling the founders of FoondaMate to build and iterate quickly. Building with Llama is helping them create an even greater impact for the 3 million students who use their fast-growing, always-on study aid in emerging markets today. More on how FoondaMate builds with Llama ➡️ https://go.fb.me/nq7026

Newly published today in Nature: No Language Left Behind is an AI model created by researchers at Meta capable of translation between 200 languages — including low-resource languages. NLLB-200 includes 200 languages, contains three times as many low-resource languages as high-resource languages and performs 44% better than prior systems. This work aims to give people the opportunity to access and share web content in their native language, and communicate with anyone, anywhere, regardless of their language preferences. Read more in Nature ⬇️

10 examples of how developers and researchers are using Meta Llama 3 to accelerate workflows for digital health and life sciences.

Want to dig into more in-depth information on Meta Llama 3? We've shared more details in the model card on GitHub ➡️ https://go.fb.me/s4k825 We also plan to publish a detailed research paper in the coming months.

Save the date! Meta Connect is happening Sept 25-26. More details: https://bit.ly/4c7SQlT

Want to start building with Meta Llama? We've published a new series of step-by-step tutorials to walk you through how to get started with Llama 3 on Linux, Windows, Mac and more. Watch the videos on YouTube ➡️ https://go.fb.me/fiq831