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Archive for the ‘AI’ Category

lafferty-mansueto

John Lafferty in the Mansueto Library. (Photo by Jason Smith)

Learning a subject well means moving beyond the recitation of facts to a deeper knowledge that can be applied to new problems. Designing computers that can transcend rote calculations to more nuanced understanding has challenged scientists for years. Only in the past decade have researchers’ flexible, evolving algorithms—known as machine learning—matured from theory to everyday practice, underlying search and language-translation websites and the automated trading strategies used by Wall Street firms.

These applications only hint at machine learning’s potential to affect daily life, according to John Lafferty, the Louis Block Professor in Statistics and Computer Science. With his two appointments, Lafferty bridges these disciplines to develop theories and methods that expand the horizon of machine learning to make predictions and extract meaning from data.

“Computer science is becoming more focused on data rather than computation, and modern statistics requires more computational sophistication to work with large data sets,” Lafferty says. “Machine learning draws on and pushes forward both of these disciplines.”

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r-BLOOMBERG4-large570A CITY PROJECT BATTLE ROYALE

As the keynote speaker at the Urban Sciences Research Coordination Network kickoff last Friday, the City of Chicago’s Brett Goldstein presented a blizzard of exciting city projects at various states of development. One slightly-under-wraps project Goldstein touched upon was the SmartData platform, an ambitious plan to craft a new tool for decision-making and city services out of the abundant raw material of city data. In collaboration with the Computation Institute and the Urban Center for Computation and Data, the city’s Innovation and Technology team hopes to create a tool that will analyze the city’s many large datasets in real time to help the city respond to challenges more quickly and efficiently, while providing frequently updated, useful information to its citizens.

Wednesday, that exciting new effort was announced as a finalist in the Bloomberg Philanthropies Mayors Challenge, a competition among ideas proposed by cities across the United States. As part of the judging, the public is invited to vote for their favorite project among the 20 finalists at the Huffington Post. We’re biased of course, but to help make the case for Chicago’s project, you can read more about the SmartData platform here, or watch a video about the concept featuring Mayor Rahm Emanuel below.

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Last October, we helped celebrate Petascale Day with a panel on the scientific potential of new supercomputers capable of running more than a thousand trillion floating point operations per second. But the ever-restless high performance computing field is already focused on the next landmark in supercomputing speed, the exascale, more than fifty times faster than the current record holder (Titan, at Oak Ridge National Laboratory). As with the speed of personal computers, supercomputers have been gaining speed and power at a steady rate for decades. But a new article in Science this week suggested that the path to the exascale may not be as smooth as the field has come to expect.

The article, illustrated with an image of a simulated exploding supernova (seen above) by the CI-affiliated Flash Center for Computational Science, details the various barriers facing the transition from petascale to exascale in the United States and abroad. Government funding agencies have yet to throw their full weight behind an exascale development program. Private computer companies are turning their attention away from high performance computing in favor of commercial chips and Big Data. And many experts agree that supercomputers must be made far more energy-efficient before leveling up to the exascale — under current technology, an exascale computer would use enough electricity to power half a million homes.

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