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Why football, not chess, is the true final frontier for robotic artificial intelligence

#artificialintelligence

First was the Monte Carlo tree search, an algorithm that rather than attempting to examine all possible future moves instead tests a sparse selection of them, combining their value in a sophisticated way to get a better estimate of a move's quality. The second was the (re)discovery of deep networks, a contemporary incarnation of neural networks that had been experimented with since the 1960s, but which was now cheaper, more powerful, and equipped with huge amounts of data with which to train the learning algorithms. The combination of these techniques saw a drastic improvement in Go-playing programs, and ultimately Google DeepMind's AlphaGo program beat Go world champion Lee Sedol in March 2016. Now that Go has fallen, where do we go from here? Following Kasparov's defeat in 1997, scientists considered that the challenge for AI was not to conquer some cerebral game.


Why football, not chess, is the true final frontier for robotic artificial intelligence

#artificialintelligence

First was the Monte Carlo tree search, an algorithm that rather than attempting to examine all possible future moves instead tests a sparse selection of them, combining their value in a sophisticated way to get a better estimate of a move's quality. The second was the (re)discovery of deep networks, a contemporary incarnation of neural networks that had been experimented with since the 1960s, but which was now cheaper, more powerful, and equipped with huge amounts of data with which to train the learning algorithms. The combination of these techniques saw a drastic improvement in Go-playing programs, and ultimately Google DeepMind's AlphaGo program beat Go world champion Lee Sedol in March 2016. Now that Go has fallen, where do we go from here? Following Kasparov's defeat in 1997, scientists considered that the challenge for AI was not to conquer some cerebral game.


Cédric Villani: Which will win out – robots or human beings?

#artificialintelligence

Which will win out – robots or human beings? This is a highly topical question. The South Koreans, and many more millions of curious people worldwide, became obsessed with this issue when a match was played between a professional Go player named Lee Se-Dol, and AlphaGo, a computer programme developed by Google subsidiary DeepMind. The match resulted in a 4-1 victory for the machine over the Korean star player. Given that Go was one of the last bastions of the games world to hold out against the learning and analysis techniques employed by cutting-edge computers, this defeat basically symbolises the considerable progress made by deep learning.


Sure you're not a robot? Solve this chess puzzle and prove it.

Mashable

Check out the chess board above--looks wrong, right? If you've ever played chess, you know something's amiss, here. For one thing, someone chose to exchange a pawn for another bishop instead of a queen. For another, virtually all the action's moved to the left side of a board. It's hard to imagine how the game got here--it's even harder to imagine what happens next, let alone a scenario in which four white pawns and a white king could play to a draw, or even win this game.


Artificial intelligence brings its brains and money to London

#artificialintelligence

Deep in the heart of Imperial College, London, a computer is learning how to play Pac-Man. Like many humans, it struggles to get the hang of the classic 1980s video game at first. With time though, experience helps it decide which manoeuvres will allow it to evade the clutches of a relentless gang of animated ghosts. This is just one of dozens of artificial intelligence (AI) projects slowly transforming the UK into the global hub for a technology that elicits fascination and fear in equal measure. The point of teaching a computer to master Pac-Man is to help it "think" and learn like a human.