Vasik Rajlich: Game Boy

Dream Jobs 2007

4 min read

Every chess player in search of a title eventually comes to Budapest, which offers more access to the necessary qualifying tournaments than any other city in the world.

So in late 1999, when he was 28 years old—a time in life when a chess player must reach for the brass ring or forever let it go—Vasik Rajlichdecided to come to these quaintly cobbled streets. The MIT-trained computer scientist told his boss, at a military-oriented research outfit in Ann Arbor, Mich., that he was taking a six-month leave of absence to score some tournament successes and raise his chess rating—a handicap based on a weighted average of one’s results against other rated players.

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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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