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Where Computing Hits the Wall: 3 Things Holding Us Back


Another way of hitting a wall.

Significant challenges still face data analytics, according to U.S. Intelligence Advanced Research Projects Activity director Jason Matheny.

Credit: Government Computer News

Jason Matheny, director of the U.S. Intelligence Advanced Research Projects Activity (IARPA), recently warned that in order for data analytics to come into its own, significant challenges in three areas still need to be addressed.

The first of these areas, according to Matheny, is the computing capacity and energy efficiency of high-performance computing facilities. He noted using current techniques and technologies, exascale computing would require a massive computing array that would consume "hundreds of megawatts of power." More efficient models are needed, and Matheny said the National Strategic Computing Initiative signed by President Barack Obama is a step in the right direction.

Matheny also noted significant advances in machine learning, but said the technology will need to develop even further to realize the potential of big data analytics.

The final challenge he highlighted was the issue of teasing causality out of big data. Current analytic models can only point out correlations, while determining causality remains beyond them. Matheny said if those capabilities are not developed, "then all of those exaflop-scale machines and all of those learning algorithms may be of limited value."

From Government Computer News
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