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Is DeepMind’s MuZero ready for the real world?

Since launching to production on a portion of YouTube’s live traffic, we’ve demonstrated an average 4% bitrate reduction across a large, diverse set of videos.
In 2016, DeepMind’s AlphaGo defeated the 18-time world champion of Go, Lee Sedol— a watershed moment in the evolution of AI. DeepMind’s computer programs like AlphaGo, AlphaZero, AlphaStar, Player of Games and MuZero have surpassed human level performances in Atari games and board games like Go, Chess and shogi. Now, DeepMind is taking it up a notch, stepping out of the research domains, and into the real-world. MuZero,with its ability to master several games with little predefined knowledge, is a significant step in DeepMind’s pursuit of general-purpose algorithms. The computer program leverages reinforcement learning to come up with winning strategies in uncharted environments.  MuZero’s RL for sequential decision making Planning effectively in unknown and complex
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Picture of Avi Gopani
Avi Gopani
Avi Gopani is a technology journalist that seeks to analyse industry trends and developments from an interdisciplinary perspective at Analytics India Magazine. Her articles chronicle cultural, political and social stories that are curated with a focus on the evolving technologies of artificial intelligence and data analytics.
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