Intel Takes Aim at "Cool Technology"

The chip giant has a new CEO and a brand new structure

1 min read
Intel Takes Aim at "Cool Technology"

When I last wrote about Intel, exactly 30 days ago, the company had yet to announce a replacement for outgoing CEO Paul Otellini, and there a was a lot of speculation about the company's direction. 

A lot can change in a month. On 2 May, Intel announced the promotion of 30-year Intel veteran Brian Krzanich to the chief executive role. And earlier this week, Reuters broke the news of a "sweeping" reorganization. Krzanich himself will now directly oversee most of the main product groups, including the company's PC and mobile units. He has also formed a "new devices" group. Mobile chip guru and Palm and Apple veteran Mike Bell has reportedly been tapped to head it up

What will this "new devices" unit do exactly?  AllThingsD says it will focus at least in part on "ultra-mobile products" and quotes a statement from the company that "the group will be tasked with turning cool technology and business model innovations into products that shape and lead markets". PCWorld speculates the new group will focus less on playing catch-up in the smartphone and tablet markets (which are still dominated by ARM-aligned companies) than on jazzier new products, such as Google Glass.

But Intel has invested a lot in its pursuit of the mobile market. Earlier this month—what a busy month!—the company unveiled Silvermont, a chip architecture that is optimized for power consumption. We'll likely have to wait until at least the end of the year, when the first chips in the Silvermont family ship, to see whether all that hard work has paid off. 

(Photo: Robert Galbraith/Reuters)

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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
Image of a computer rendering.

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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