Stefan Mileschin

Machine learning systems have been mopping the floor with their human opponents for well over a decade now (seriously, that first Watson Jeopardy win was all the way back in 2011), though the types of games they excel at are rather limited. Typically competitive board or video games using a limited play field, sequential moves and at least one clearly-defined opponent, any game that requires the crunching of numbers is to their advantage. Diplomacy, however, requires very little computation, instead demanding players negotiate directly with their opponents and make respective plays simultaneously — things modern ML systems are generally not built to do. But that hasn't stopped Meta researchers from designing an AI agent that can negotiate global policy positions as well as any UN ambassador.

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