Just What Do You Think You're Doing, Dave?

How Apollo's astronauts learned to work with--and around--their computers

2 min read

In 1961, the average rocket-borne computer ran on average for 15 hours before an electronics ­failure crashed it. That ­dismal ­performance record didn’t matter much to the ­military, whose suborbital ­missiles required only ­minutes of computer on-time. But a manned moon shot required that computers run 1500 hours between failures.

As David Mindell points out in Digital Apollo: Human and Machine in Spaceflight , NASA’s project managers not only met that 1500-hour goal but greatly overshot it. When Neil Armstrong and his compatriots strode on the lunar surface between 1969 and 1972, the total mean time between ­failures of the onboard computers turned out to be closer to 50 000 hours.

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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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