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Is Production RL at a tipping point?

Posted Apr 12
# Open Source
# Research
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SPEAKER
Dr. Waleed Kadous
Dr. Waleed Kadous
Dr. Waleed Kadous
Head of Engineering @ Anyscale

Dr. Waleed Kadous leads engineering at Anyscale, the company behind the open source project Ray. Prior to Anyscale, Waleed worked at Uber, where he led overall system architecture, evangelized machine learning, and led the Location and Maps teams. He previously worked at Google, where he founded the Android Location and Sensing team, responsible for the "blue dot" as well as ML algorithms underlying products like Google Fit.

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Dr. Waleed Kadous leads engineering at Anyscale, the company behind the open source project Ray. Prior to Anyscale, Waleed worked at Uber, where he led overall system architecture, evangelized machine learning, and led the Location and Maps teams. He previously worked at Google, where he founded the Android Location and Sensing team, responsible for the "blue dot" as well as ML algorithms underlying products like Google Fit.

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SUMMARY

Reinforcement Learning has historically not been as widely adopted in production as other learning approaches (particularly supervised learning), despite being capable of addressing a broader set of problems. But we are now seeing an exponential growth in production RL applications: so much so that it looks like production RL is about to reach a tipping point to the mainstream. In this talk, weÕll talk about why this is happening; detail concrete examples of the areas where RL is adding value; and share some practical tips on deploying RL in your organization.

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