California Dreamin'

Spectral lines

3 min read

While archrival Microsoft hemorrhages cash and employees, Google is mapping out its plan for benevolent world domination. The company is flush, with US $16 billion in cash at press time, and its investment in new and existing projects constitutes a miniature economic-stimulus package unto itself. In November it was the Google Android cellphone. Last month it was the new interactive maps Google Earth Ocean and Google Mars, as well as Google Latitude, which allows subscribers to locate each other anytime, anywhere. And then there’s the new Chrome Web browser. Clearly, Google’s investment in R&D—$2.1 billion in 2007, according to IEEE Spectrum’s latest R&D 100 survey [PDF]--is bearing some luscious, and potentially lucrative, fruit.

But not every idea coming out of Google is a home run. Sometimes it’s a punch line to a joke waiting to happen. Witness the company’s recent investment in Ray Kurzweil’s Singularity University. The amount of money is insignificant by Google’s standards—at a minimum of $250 000 (the Corporate Founder level), it’s less than a thousandth of one percent of cash on hand. The effect on the company’s good name might prove to be less trivial.

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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
DarkBlue1

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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