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In a watershed moment for cryptography, computer scientists have proposed a solution to a fundamental problem called “program obfuscation.”
The nature of computing has changed dramatically over the last decade, and more innovation is needed to weather the gathering data storm.
New technologies have launched the life sciences into the age of big data. Biologists must now make sense of their windfall.
Scientific data sets are becoming more dynamic, requiring new mathematical techniques on par with the invention of calculus.
As physics prepares for ambitious projects like the Large Synoptic Survey Telescope, the field is seeking new methods of data-driven discovery.
As science dives headlong into an ocean of data, the demands of large-scale interdisciplinary collaborations are growing increasingly acute.
How do you know if a quantum computer is doing what it claims? A new protocol offers a possible solution and a boost to quantum cryptography.
Studies show that computer models called “neural networks” behave strikingly similar to actual brains when performing certain tasks, suggesting the two may learn in the same way.
As the role of computers in pure mathematics grows, researchers debate their reliability.