Artificial Intelligence Still Has a Long Way to Go

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goby Angela Guess

Jonathan Vanian recently wrote in Fortune, “Computers can recognize cats in photos and translate websites into different languages thanks to recent advances in artificial intelligence. But that’s just the tip of the iceberg when it comes to someday creating computers that can think like humans. Take the example of Google’s AlphaGo computer system, which managed to defeat a human at the ancient Chinese board game Go. But applying a similar kind of artificial intelligence in other situations will be difficult, explained Oren Etzioni, the CEO of the Allen Institute for Artificial Intelligence, a technology research organization. Etzioni made the comments Monday at an MIT Tech Review conference in San Francisco about cutting-edge technologies. He was joined by fellow artificial intelligence experts from Google and the Chinese search company Baidu.”

Vanian goes on, “Go, the game, is incredibly complex with more possible positions on the board than the number of atoms in the universe, Etzioni explained. But Go is still a board game, whereas the nuances of human language is far more complex and is difficult for even the best computer systems to understand, Etzioni said. Just because AlphaGo defeated a human doesn’t mean that humans were uninvolved in its victory, he said. Humans still built the so-called neural networks used to train AlphaGo, and they were the ones who decided to feed it the data it required to learn how to play, Etzioni said. ‘Machine learning is still 99% human work,’ Etzioni said, referring to machine-learning algorithms, a subset of artificial intelligence technologies that has grown in popularity in recent years.”

Read more here.

Photo credit: Flickr

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