Llama, Scaling Up LLMs in an Open Ecosystem

Llama and Llama 2 have taken the Generative AI world by storm with publicly available state of the art performance under a commercially permissive license. This has been a game changer for startups, enterprises and a community looking to harness the power of Generative AI but need a platform to build on. Llama is that platform. Join Joe Spisak on a journey through the evolution of Llama — Meta’s latest open source large language model (LLM). Understand its growth and the range of available models including the most recently released Code Llama. Joe will also dive deeper into some of the major platforms built on Ray that enabled Llama 2 and Code Llama such that you yourself can leverage state of the art performance on infrastructure along with the most popular open models available.

About Joe Spisak:
Joe Spisak is Product Director and Head of Open Source in Meta’s Generative AI organization including Llama. A veteran of the AI space with over 10 years experience, Joe led product teams at Meta/Facebook, Google and Amazon where he focused on open source AI, open science and building developer tools such as PyTorch to help the community scale up AI in an open and collaborative way. As the leader of product for PyTorch, he and the team built an amazing platform and community that made PyTorch the leading open source AI development framework in the industry and took it to the Linux Foundation where it now resides in partnership with Microsoft, Nvidia, AMD, Google, Amazon and others. Joe is also an angel and advisor to companies like Anthropic, Lastmile.AI, Lightning.AI, and others.
LinkedIn:   / jspisak  
Twitter:   / joespeez  

Find the slide deck here: https://drive.google.com/file/d/1iErx...

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About Anyscale
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Anyscale is the AI Application Platform for developing, running, and scaling AI.

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About Ray
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Ray is the most popular open source framework for scaling and productionizing AI workloads. From Generative AI and LLMs to computer vision, Ray powers the world’s most ambitious AI workloads.

https://docs.ray.io/en/latest/

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