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What Chess Teaches Us About Reinforcement Learning - Richard Sutton
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The Long Game in Startups
Richard Sutton discusses the concept of long-term rewards in startups, comparing it to the learning process in chess. He emphasizes how humans can break down a decade-long goal into intermediate steps, similar to how chess players learn from short-term actions like capturing pieces. This segment highlights the importance of understanding the relationship between immediate actions and long-term outcomes in both entrepreneurship and reinforcement learning.
"Suppose a human is trying to make a startup and this is a thing which has a reward on the order of 10 years. Once in 10 years you might have an exit where you get you know paid out a billion dollars. ..."
The Long Game: Startups and Chess
Richard Sutton draws parallels between the long-term goals of startups and the game of chess, emphasizing the importance of intermediate steps in achieving significant rewards. He explains how humans can navigate complex processes by understanding short-term actions that contribute to a grander objective, similar to how chess players learn from immediate moves to enhance their chances of winning.
"Suppose a human is trying to make a startup and this is a thing which has a reward on the order of 10 years. Once in 10 years you might have an exit where you get you know paid out a billion dollars. ..."