DailyDirt: Winning Isn't Everything (original) (raw)

from the urls-we-dig-up dept

Not that long ago, we mentioned that progress towards an algorithm that could play the game of Go better than humans was on the horizon. It looks like our wetware shouldn’t be too smug about being able to play Go now, but we can still have fun playing, right? And it’ll still take a while before robots are any good at (non-contact) sports. Ping pong, FTW!

• Google has announced that its machine learning system AlphaGo has beaten a human expert in 5 games. That’s impressive, considering that all other attempts haven’t been able to reliably defeat amateur players. In March, AlphaGo is scheduled to play a top player in the world, Lee Sedol, to really test its abilities. And hopefully, this time the human player will lose more gracefully without accusing the computer’s side of cheating. [url]
• There are some games that you can play to win, but it’s not a very fun experience. Try playing Monopoly ruthlessly. If you played Monopoly as a kid, you probably didn’t learn the rules correctly. And you probably up-ended the board to end the game. [url]
• Ideally, we humans should take advances in machine learning as an opportunity for more human-machine cooperation to solve the world’s most dire problems. Together, machines and people should be able to solve the “wicked” hard problems of poverty, pollution, diseases and more. Maybe we can convince the robots to help us. [url]
• Oh. And Facebook’s effort to get a computer playing Go that can beat humans is “getting close” — but maybe it can get exponentially better by March? The guy sitting a few feet from Mark has a bit of time to really get his algorithms working. Or maybe it should challenge Alphago to a match to see how the two compare. [url]

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Filed Under: algorithms, alphago, artificial intelligence, deep learning, game algorithms, games, go, machine learning, monopoly
Companies: google