August 23-24 | San Francisco


Developers, researchers, and engineers are using Ray to build the next generation of scalable AI and machine learning applications. Ray Summit brings the community together to build, learn, and explore everything AI and more on Ray.

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Get ready for two days of epic Ray talks, community celebrations, and deep-dive technical content. No matter your level of experience with Ray, you’ll come away with tools and know-how that will help you to build and deploy large-scale AI and ML applications.

Keynote Speakers


Smitha Shyam

Director of Engineering, Uber

Soumith Chintala

Engineer, Meta AI

Anca Dragan

Assistant Professor, UC Berkeley

Darío Gil

Senior Vice President and Director of Research, IBM

Kim Hazelwood

Engineering Director, Meta AI

Greg Brockman

CTO & Co-Founder, OpenAI
Ion Stoica

Ion Stoica

Co-Founder, Executive Chairman & President, Anyscale | Professor, UC Berkeley
Robert Nishihara

Robert Nishihara

Co-founder and CEO, Anyscale
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Exclusive Ray Training Sessions

Ray Summit is a great opportunity to level up your Ray skills through hands-on training sessions with the builders and maintainers of Ray. We’re offering several pre-conference training sessions on August 22. Space is limited — reserve your spot now!


Training 1:

Introduction to Ray for distributed applications

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Training 2:

Machine learning model deployment and serving with Ray Serve

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Training 3:

Introduction to reinforcement learning and RLlib

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Why Attend?

As the annual user conference for the open source Ray community, Ray Summit is a unique opportunity to enhance your Ray skills, build your professional network, and learn what's on the Ray roadmap.

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Enhance Your Skills

Extend what you can do with Ray by attending hands-on, expert-led workshops and deep dives

See the agenda
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Build Your Network

Mingle with the world’s top minds in distributed computing, machine learning, and AI

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Get Involved

Learn what’s on the Ray roadmap and connect with the builders and maintainers of Ray and Ray libraries

What People Are Saying About Ray

We chose Ray as the unified compute backend for our machine learning and deep learning platform because it has allowed us to significantly improve performance and fault tolerance, while also reducing the complexity of our technology stack. Ray has brought significant value to our business.

Xu Ning, Senior Manager, Uber AI Platform
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Ready to Register?

Come connect with the global community of thinkers and disruptors who are building and deploying the next generation of AI and ML applications.

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Join the Conversation

Ready to get involved in the Ray community before the conference? Ask a question in the forums. Open a pull request. Or share why you’re excited with the hashtag #RaySummit on Twitter.