All Posts

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05 . 05 . 2022

Handling files and packages on your cluster with Ray runtime environments

By Archit Kulkarni and 
Edward Oakes
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05 . 03 . 2022

Riot Games and deep reinforcement learning in gaming

By Erik Martinez
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05 . 03 . 2022

Reinforcement learning based on market simulation at JPMorgan

By Erik Martinez
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05 . 03 . 2022

Smart supply chain management with reinforcement learning at Dow

By Erik Martinez
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05 . 03 . 2022

Siemens brings reinforcement learning to energy, transportation and logistics

By Erik Martinez
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04 . 26 . 2022

What is distributed training?

By Keith Pijanowski and 
Michael Galarnyk
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04 . 19 . 2022

New in KubeRay 0.2.0: Autoscaling (alpha), simplified installation, and more

By Jiaxin Shan and 
KubeRay Team
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04 . 14 . 2022

Ray 1.12: Ray AI Runtime (alpha), usage data collection, and more

By Paige Bailey, 
Richard Liaw, 
Jian Xiao and 
Chandler Gibbons
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04 . 06 . 2022

Biggest takeaways from our RL tutorial: Long-term rewards, offline RL, and more

By Christy Bergman
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03 . 24 . 2022

Large-scale distributed training with TorchX and Ray

By Mark Saroufim and 
Jules S. Damji
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03 . 23 . 2022

Ray Summit 2022 Call for Papers is now open

By Jules S. Damji and 
Chandler Gibbons
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03 . 22 . 2022

5 reasons to attend this month’s Production RL Summit

By Chandler Gibbons
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03 . 15 . 2022

Redis in Ray: Past and future

By Mingwei Tian
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03 . 09 . 2022

Ray 1.11: Redisless Ray, a docs redesign, and Python 3.9 support

By Mingwei Tian and 
Chandler Gibbons
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03 . 03 . 2022

Practical tips for training Deep Q Networks

By Misha Laskin