Most recent advances in artificial intelligence — such as mobile apps that convert speech to text — are the result of machine learning, in which computers are turned loose on huge data sets to look for patterns.
To make machine-learning applications easier to build, computer scientists have begun developing so-called probabilistic programming languages, which let researchers mix and match machine-learning techniques that have worked well in other contexts. In 2013, the U.S. Defense Advanced Research Projects Agency, an incubator of cutting-edge technology, launched a four-year program to fund probabilistic-programming research.
At the Computer Vision and Pattern Recognition conference in June, MIT researchers will demonstrate that on some standard computer-vision tasks, short programs — less than 50 lines long — written in a probabilistic programming language are competitive with conventional systems with thousands of lines of code.
“This is the first time that we’re...
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