Daniel Mankowitz

Daniel Mankowitz

Daniel Mankowitz is a Staff Research Scientist at Google Deepmind, working on solving the key challenges that will unlock Reinforcement Learning algorithms to work on real-world applications at scale. This includes a focus on Reinforcement Learning from Human Feedback (RLHF) in the context of Large Language Models (LLMs). Mankowitz has worked on: code optimization, code generation, video compression, recommender systems, and controlling physical systems such as Heating Ventilation and Air-Conditioning (HVAC), with publications in Nature and Science. 

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  • Organization
    Google DeepMind
  • Profession
    Staff Research Scientist
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OnlineGOAL 1GOAL 10+15
20 July 2023
17:00 - 18:30
EST - New York
CST - Beijing
PST - Los Angeles
AWST - Perth, Australia
We engage with core computer algorithms such as “sorting” for...