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time is up

RL Research-to-RealLife Gap Panel

Ask experts questions about the RL Research-to-RealLife Gap. Panelists: Hasham Burhani (RBC Capital Markets), Craig Buhr (MathWorks), Jeff Mendenhall (Microsoft), Xiaocheng Tang (Didi), Yang Yu (Polixir.ai / Nanjing U.); Co-Chairs/Moderators: Matthew E. Taylor (U. of Alberta) and Kathryn Hume (Borealis AI). Panel discussion time: 20:00-21:00, July 23 EDT (Boston time). https://sites.google.com/view/RL4RealLife


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What staffing considerations would a new company have. Should you upskill? Hire a data scientist? Hire a general ML person? Hire a RL person?
 
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Tes Shizume
When heuristics are already exist in your systems, how do you tell whether it is worth using RL to replace that existing solutions?
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How did you identify RL as a solution for a new or existing problem?
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What was the path from research to prototype to deployment?
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How did you choose between the different existing frameworks / pipelines vs. building your own?
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Is it difficult to get buy-in from management to deploy RL? How is it different from deploying traditional supervised learning models?
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What advice would you have for a company interested in adding RL to its toolbox?
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What level of AI/ML maturity is needed before a company should consider using RL?
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What kind of compute resources would you recommend?
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What kind of collaboration with academia, if any, would be most beneficial to you? To companies getting started in RL?
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