The phrase "Quantum computing" sounds like something from a science fiction show, but it's very real. Some federal agencies are already investing in it and more are sure to follow. Agency leaders need to understand what it is, how it differs from the traditional computer technology everyone uses, and what to do in order to implement it. Put as simply as possible, Quantum computing uses quantum mechanics to perform computation. These phenomena enable certain kinds of calculations at a speed and scale that conventional computers cannot come close to matching. However, much of its potential remains theoretical as scientists continue to refine the technology.

If anyone is qualified to talk about the machine-learning revolution currently underway it's Terry Sejnowski. Long before the virtual assistant Alexa was a glint in Amazon's eye or self-driving cars were considered remotely feasible, Professor Sejnowski was laying the foundations for the field of deep learning. Sejnowski was one of a small group of researchers in the 1980s who challenged the prevailing approach to building artificial intelligence and proposed using mathematical models that could learn skills from data. SEE: IT leader's guide to deep learning (Tech Pro Research) Today those brain-inspired, deep-learning neural networks have led to major breakthroughs in machine learning: giving rise to virtual assistants that increasingly predict what we want, on-demand translation and computer vision systems that allow self-driving cars to "see" the world around them. But Sejnowski says the machine learning is very much in its infancy, comparing it to the rudimentary aircraft that the Wright brothers flew in the US town of Kitty Hawk at the turn of the 20th century.

Microsoft is using custom hardware to realize a 50-100x speed up in how quickly it can run AI algorithms that power its Bing search engine -- and will make the tech available to all from next year. The acceleration is being powered by the BrainWave platform, a network of customizable chips known as Field-Programmable Gate Arrays (FPGAs), tailored to efficiently handle deep neural networks. "The power of the BrainWave platform are FPGAs, field-programmable gate arrays, which are really executing these AI algorithms in hardware," said Joseph Sirosh, corporate VP for artificial intelligence & research at Microsoft. "What this means is approximately 50-100x the speed up. Also, there's significant cost savings, because you are executing these neural networks in the most efficient way possible in hardware."