Can a Machine Think?

Can a Machine Think? The Turing Test, homophones, and language are discussed as Byron examines this question in this episode of The AI Minute. For more on Artificial Intelligence: https://voicesinai.com https://gigaom.com https://byronreese.com https://amzn.to/2vgENbn... Transcript: You've probably heard of the Turing test, which Alan Turing put forth decades ago when he asked the question, “Can a machine think?” He proposes a test where a person sitting at a terminal typing questions and receiving answers can't really tell whether they’re talking to a human or to a machine. Turing says that if the computer can fool the human into thinking that it's a person 30% or more of the time, then we have to say that machine is thinking. The Turing test is often derided and people question whether it really means something, but it undoubtedly does. Language is a big part of what makes humans smart and intelligent and able to communicate. And a computer being able to master it, to be able to infer all the subtleties that come with language, would be a major Milestone indeed. That being said we're incredibly far away from having any system that can pass it. The question I type into every AI I come across is, “What's bigger, a nickel or the sun?” It's a tricky question - the sun is a homophone it could be s-u-n or s-o-n, and nickel is a metal as well as a 5 cent piece, and all of those ambiguities are such that I've never seen a system that understood the question, let alone could answer it correctly. One final note: the 30% number of Turing's is pretty interesting. You might wonder why it wouldn't be 50%, why the machine wouldn't need to be able to convince you it's a person half the time. I think Turing thought that bar would be too high. The question isn’t can a machine think as well as a human, but can a machine think at all. Now, the really interesting idea is that if a machine ever gets picked more than 50% of the time, the conclusion you have to draw is that it's better at seeming like a human than we are. http://bit.ly/2UE7OYu gigaom April 24, 2019 at 03:04PM