Light-based computer may parallelize 10-megabit computations

Light-based computer may parallelize 10-megabit computations

Enlarge / If everything’s set up properly, you know you have a solution when the input light results in a single point of light as the output. (credit: Robert Horn/Argonne National Laboratory)

When it comes to computation, the modern approach seems to involve an enormous bucket of bits, vigorous shaking, and not a lot of explanation of how it all works. If you ever wondered how Excel became such an abomination, now you know.

We don’t seem to have a problem creating and filling enormous buckets of bits, but shaking them up is energy-intensive and slow. Modern processors, as good as they are, simply don’t cope well with some problems. A light-based, highly parallel processor may just be the (rather bulky) co-processor that we’ve been looking for to handle these tasks.

Solutions are downhill

One way to compute a solution to a problem is called annealing. I’ve written a

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Optical neural network at 50zJ per op? Nope, but it’s still a good idea

Optical neural network at 50zJ per op? Nope, but it’s still a good idea

Enlarge (credit: BeeBright/Getty Images)

Artificial intelligence (AI) has experienced a revival of pretty large proportions in the last decade. We’ve gone from AI being mostly useless to letting it ruin our lives in obscure and opaque ways. We’ve even given AI the task of crashing our cars for us.

AI experts will tell us that we just need bigger neural networks and the cars will probably stop crashing. You can get there by adding more graphics cards to an AI, but the power consumption becomes excessive. The ideal solution would be a neural network that can process and shovel data around at near-zero energy cost, which may be where we are headed with optical neural networks.

To give you an idea of the scale of energy we’re talking about here, a good GPU uses 20 picoJoules (1pJ is 10-12J ) for each multiply and accumulate operation. A

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