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Judea Pearl, a pioneering figure in artificial intelligence, argues that AI has been stuck in a decades-long rut. His prescription for progress? Teach machines to understand the question why.
To efficiently analyze a firehose of data, scientists first have to break big numbers into bits.
The computational immunologist Purvesh Khatri embraces messy data as a way to capture the messiness of disease. As a result, he’s making elusive genomic discoveries.
To assess the ocean’s health, ecology’s “rugged individualists” learned to get with the big data program.
Machine learning works spectacularly well, but mathematicians aren’t quite sure why.
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.