Tag: Artificial Intelligence

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A.I. software masters the game of Go

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Google is set for the ultimate human-vs.-machine Go match. (Credit: Nature / Google DeepMind)

Mark another milestone in the rise of the machines: An artificial intelligence program pioneered by Google DeepMind has learned how to play the game of Go well enough to beat a human champion decisively in a fair match.

That’s a quantum leap for artificial intelligence: Go is looked upon as the “holy grail of AI research,” said Demis Hassabis, the senior author of a research paper on the project published today by the journal Nature.

The game seems simple enough, involving the placement of alternating black and white stones on a 19-by-19 grid. The object is merely to avoid having your stones hemmed in on four sides by your opponent’s stones. But Go, which originated in China thousands of years ago, is considered the world’s most complex game. “It has 10170 possible board positions, which is greater than the number of atoms in the universe,” Hassabis noted.

That means a computer program can’t best humans with the same kind of approach used for checkers and and chess. The programs for those games combine brute-force searches through the possible moves with a weighted evaluation of patterns in moves. But researchers at Google DeepMind say their software, known as AlphaGo, takes a different approach.

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A.I. pioneer Marvin Minsky dies at age of 88

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MIT Professor Emeritus Marvin Minsky has died at 88. (Credit: Louis Fabian Bachrach via MIT)

Marvin Minsky, the computer scientist who helped blaze the trail for virtual smartphone assistants and other manifestations of artificial intelligence, died of a cerebral hemorrhage on Sunday at the age of 88.

Word of Minsky’s passing came today from his family as well as from the Massachusetts Institute of Technology, where Minsky worked on the foundations of A.I. since the 1950s.

As the co-founder of MIT’s Artificial Intelligence Laboratory, now known as theComputer Science and Artificial Intelligence Laboratory, Minsky contributed to the decades-long drive to make machines more humanlike – through the development of robotic hands and neural networks, as well through his musings on the philosophical underpinnings of intelligence.

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Experts find quicker way to teach a computer

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This illustration gives a sense of how characters from alphabets around the world were replicated through human vs. machine learning. (Credit: Danqing Wang)

Researchers say they’ve developed an algorithm that can teach a new concept to a computer using just one example, rather than the thousands of examples that are traditionally required for machine learning.

The algorithm takes advantage of a probabilistic approach the researchers call “Bayesian Program Learning,” or BPL. Essentially, the computer generates its own additional examples, and then determines which ones fit the pattern best.

The researchers behind BPL say they’re trying to reproduce the way humans catch on to a new task after seeing it done once – whether it’s a child recognizing a horse, or a mechanic replacing a head gasket.

“The gap between machine learning and human learning capacities remains vast,” said MIT’s Joshua Tenenbaum, one of the authors of a research paper published today in the journal Science. “We want to close that gap, and that’s the long-term goal.”

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Let Google’s A.I. bot answer your emails

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Google’s Smart Reply feature analyzes incoming email with an encoder. (Google image)

Weary of spambots, robo-calls and Twitter bots? Google is coming out with an artificial-intelligence tool that’s on your side for a change: Smart Reply, a feature that’s built into its Inbox app for Android and iOS.

Smart Reply is designed to take the thumbwork out of replying to email on a mobile device.

“I get a lot of email, and I often peek at it on the go with my phone. But replying to email on mobile is a real pain, even for short replies,” Greg Corrado, a senior research scientist at Google, writes on the company’s research blog. “What if there were a system that could automatically determine if an email was answerable with a short reply, and compose a few suitable responses that I could edit or send with just a tap?”

Corrado explains at length how Google’s engineers developed a deep neural network that analyzes incoming email and suggests short responses based on context.

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