Neuroevolution: an alternative route to Artificial Intelligence

See on Scoop.itTracking the Future

If you were to ask a random person what the best example of Artificial Intelligence is out there, what do you think it would be?

Most likely, it would be IBM’s Watson.

In a stunning display of knowledge and accuracy, Watson blew away the world Jeopardy champions Ken Jennings and Brad Rutter without blowing a fuse, and ended with Jennings proclaiming, “I for one welcome our new computer overlords.”

IBM’s Watson represents the current popular approach to AI: that is, spending hundreds of hours hand-coding and fine-tuning a program to perform exceedingly well on a single task. Most people in the field of AI call machines like Watson an expert system because they are designed to be experts at a single task. This approach has been wildly successful lately, producing machines that drive cars and fly UAVs by themselves, beat world chess and Jeopardy champions, and even fool some people into thinking they’re human.

However, imagine how hard it would be to hand-code a system that could do everything the human brain is capable of. Do you think that sounds impossible? That’s the reason why the field of neuroevolution was born: scientists wanted to harness the creative power of evolution to design the programs that could achieve human-level intelligence.

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