The Beautiful Mind of Neural Networks

A “second-best” technology moves to the center of our lives

3 min read
Illustration: Greg Mably
Illustration: Greg Mably

I was telling someone how intelligent my dog was. He shrugged dismissively and said, “Dogs are just really good pattern detectors.”

Afterward, I looked at my dog a little differently. “Are you intelligent, or just a pattern detector?” I asked her. She just wagged her tail and said nothing, and I suppose that’s open to interpretation. She swims in a sea of data from vision, sounds, and smells. From this data, she forms a model of the world—a dog’s world, and one that is unknowable to us, and yet seems to have commonalities with our own. She knows the objects and inhabitants of her world and the patterns of everyday experience and she is keenly aware of any anomalies. I once heard a speaker on intellectual property say that “your dog knows where your property ends.” I’m not sure that my dog does, but if so, it would be an example of deriving an abstract rule from patterns of behavioral data.

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The Future of Deep Learning Is Photonic

Computing with light could slash the energy needs of neural networks

10 min read

This computer rendering depicts the pattern on a photonic chip that the author and his colleagues have devised for performing neural-network calculations using light.

Alexander Sludds

Think of the many tasks to which computers are being applied that in the not-so-distant past required human intuition. Computers routinely identify objects in images, transcribe speech, translate between languages, diagnose medical conditions, play complex games, and drive cars.

The technique that has empowered these stunning developments is called deep learning, a term that refers to mathematical models known as artificial neural networks. Deep learning is a subfield of machine learning, a branch of computer science based on fitting complex models to data.

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