A writer and a software engineer from Google's People + AI Research team explore the human choices that shape machine learning systems by building competing tic-tac-toe agents.
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A writer and a software engineer from Google's People + AI Research team explore the human choices that shape machine learning systems by building competing tic-tac-toe agents.
Yannick and David’s systems play against each other in 500 games. Who’s going to win? And what can we learn about how the ML may be working by thinking about the results?
Tic-Tac-Toe the Hard Way
A writer and a software engineer from Google's People + AI Research team explore the human choices that shape machine learning systems by building competing tic-tac-toe agents.
