From Jesse Emspak at LiveScience:
What Is Intelligence? 20 Years After Deep Blue, AI Still Can’t Think Like Humans
“Good as they are, [computers] are quite poor at other kinds of decision making,” said Murray Campbell, a research scientist at IBM Research. “Some doubted that a computer would ever play as well as a top human.
“The more interesting thing we showed was that there’s more than one way to look at a complex problem,” Campbell told Live Science. “You can look at it the human way, using experience and intuition, or in a more computer-like way.” Those methods complement each other, he said.
Although Deep Blue’s win proved that humans could build a machine that’s a great chess player, it underscored the complexity and difficulty of building a computer that could handle a board game. IBM scientists spent years constructing Deep Blue, and all it could do was play chess, Campbell said. Building a machine that can tackle different tasks, or that can learn how to do new ones, has proved more difficult, he added. More.
One obvious reason is that human intelligence is far more than computational power, but the nerds will still be figuring that one out years from now.
See also: Deep learning is easy to fool? Researchers: Our results shed light on interesting differences between human vision and current DNNs, and raise questions about the generality of DNN computer vision.
Data basic: An introduction to information theory
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