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Pretty Math Problem

Computer scientists use sparse matrix values to generate beautiful images

1 min read
Pretty Math Problem

math problem matrix

Image: Yifan Hu/AT&T Labs Visualization Group
Click on image to enlarge.

You're looking at the solution to a computational fluid dynamics problem. It is one of thousands of math-based artistic renderings stored in a database maintained by computer scientists from the University of Florida, in Gainesville, and AT&T Labs Research, in Florham Park, N.J. But what you don't see makes all the difference. The matrix, or table of values, is sparse, meaning that the number of zeros it contains far outweighs the number of nonzero values. This sparsity allows for a type of data compression that lets engineers working on a simulation store the data without taking up too big a chunk of memory.

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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

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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