IEEE Spectrum

Neural Networks Can Drive Virtual Racecars Without Learning

Animals are born with innate abilities and predispositions. Horses can walk within hours of birth, ducks can swim soon after hatching, and human infants are automatically attracted to faces. Brains have evolved to take on the world with little or no experience, and many researchers would like to recreate such natural abilities in artificial intelligence.

New research finds that artificial neural networks can evolve to perform tasks without learning. The technique could lead to AI that is much more adept at a wide variety of tasks such as labeling photos or driving a car.

Artificial neural networks are arrangements of small computing elements (“neurons”) that pass information between them. The networks typically learn to perform tasks like playing games or recognizing images by adjusting the “weights” or strengths of the connections between neurons. A technique called neural architecture search tries lots of network shapes and sizes to find ones that learn better for a specific purpose.

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