Jules Damji and Richard Liaw on the state of the Ray ecosystem.
Jules Damji is lead developer advocate, and Richard Liaw is an engineering manager at Anyscale, the startup founded by the creators of Ray, the open source project that makes it simple to scale any compute-intensive Python workload. We discuss the current state of Ray, a variety of use cases, and Ray’s near-term roadmap.
Highlights in the video version:
- Introduction to Jules Damji and Richard Liaw
What is Ray and who should use it?
Integrating libraries with Ray
Impressive Ray uses cases
Where is Ray heavily being used?
Scalable and end-to-end machine learning
Highlights of new Ray features
Orchestration and Tune
Reception of Ray AI runtime
Ray Serve and Ray Dataset libraries and use cases
What’s on the upcoming roadmap?
Why should practitioners attend the Ray Summit hybrid conference?
- A video version of this conversation is available on our YouTube channel.
- Devin Petersohn: Dataframes at scale
- Machine Learning Trends You Need To Know
- Nic Hohn and Max Pumperla: Reinforcement Learning in Real-World Applications
- Jeremiah Lowin: Dataflow Automation
- Nick Schrock: Software-Defined Assets
- Haytham Abuelfutuh: Orchestrating Machine Learning Applications
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[Image: from the Ray documentation; used with permissions.]