Quantum Computing: What to Expect

SEMA News—April 2019


By Joe Dysart

Quantum Computing: What to Expect

IBM researchers at work on one of its quantum computers.

Businesses eagerly awaiting the next generation of computing—blazingly fast quantum computers—can expect to see select applications run on the uber technology as early as 2020, according to Jorg Esser, a partner at business consulting firm Roland Berger (www.rolandberger.com).

“Companies need to embrace the vision now that all data-related challenges associated with quantum computer development will be able to be resolved easily at some point in the next few years and rework their value propositions and operating models accordingly,” he said.

In fact, computing goliath IBM has already built a number of experimental quantum computers and currently offers free access to one of its fastest—via the IBM Cloud—to any researcher or company looking to take the tech for a test drive (https://quantumexperience.ng.bluemix.net/qx/community).

“Thanks to this incredible resource that IBM offers, I have students run actual quantum algorithms on a real quantum computer as part of their assignments,” said Andrew Houck, professor of electrical engineering at Princeton University. “That drives home the point that this is a real technology, not just a pipe dream.

Added Arvind Krishna, director at IBM Research: “We believe that quantum computing will provide the next powerful set of services delivered via the IBM Cloud platform and promises to be the next major technology that has the potential to drive a new era of innovation across industries.”

Businesses have been especially keen to get their hands on quantum computers ever since reports began emerging that they make today’s desktops look like Stone Age tools. For example, Google reported three years ago that a quantum computer it used in joint experiments with NASA was a hundred million times faster than a typical desktop PC, according to Hartmut Neven, Google’s director of engineering.

To fully understand how a computer can run that fast, most of us would need to go back to college and polish off that physics degree we somehow let slip away. But suffice it to say that the next-generation tech relies on quantum mechanics—a branch of physics that has concluded that an atomic particle can exist in two places simultaneously.

Yes, as mere mortals, this claim that a piece of matter—a car, say—can exist simultaneously in both Sri Lanka and New Jersey hurts the brain. But that has not stopped researchers from forging ahead and building ever-faster experimental quantum computers that will ultimately begin showing up in the commercial pipeline.

Indeed, there is something of a quantum-computing arms race underway right now, with governments, industry and academia all scrambling to popularize quantum computing. Here in the United States, for example, Google and the University of California at Santa Barbara have a joint quantum research project underway, as do Lockheed Martin and the University of Maryland.

“The United States must get there first,” said former Chairman of the House Science, Space and Technology Committee Lamar Smith (R-Texas) about the quantum-computing race.

Initially, for all but the most deep-pocketed corporations, access to bleeding-edge quantum computer power will most likely be through the cloud, where the wunderkind tech will crunch through terabytes of data at head-turning speeds. And while researchers are still working on the ways quantum computers will change how we work and live, expect to see heavy use first in machine learning applications, an insider said.

As most business leaders know, machine learning—a form of artificial intelligence that enables a computer to train itself and get better and better over time at solving the same kind of problem—is already transforming the way business is done. But we’re generally able to run machine learning applications only on classical computers these days—kids crayons when compared to quantum computers. Once those applications are unleashed on quantum computers, the power and perception of machine learning tools will increase exponentially, according to researchers.

In practical terms, that will mean that businesses running AI video surveillance software, for example—which can continuously scan a warehouse for signs of a break-in or movement in a restricted sector—will find that software will run much faster, much more efficiently, and much more perceptively.

Meanwhile, businesses running AI software that sifts their data for patterns and insights will find that those processes will be made even more powerful and even more insightful. For instance, researchers at Case Western Reserve University have developed AI software that has trained itself to be better than seasoned medical professionals at predicting heart failure, according to Anant Madabhushi, a professor of biomedical engineering and the team leader of the university’s research.

Granted, most companies are not in the business of predicting heart failure, but they sure could benefit from a super-fast computer with those kinds of perceptive and analytical skills.

One more real-world example: Turbocharged machine learning is also going to give companies much deeper insights into the health and stability of workers and enable them to make AI-aided decisions on who is right to hire for a job and who is right to keep on a job.

Machine learning software from Mindstrong Health (https://mindstronghealth.com), for example, already enables users to identify if a person is a schizophrenic simply by analyzing how that person works on a keyboard, millisecond by millisecond.

“We believe that digital biomarkers are the foundation for measurement-based mental health care,” said Paul Dagum, Mindstrong Health’s CEO.

Similar keystroke-analysis software is being developed by Neurametrix (www.neurametrix.com/how) that can detect if a person has contracted Parkinson’s disease.

Yes, there’s a creep factor involved here, for sure. But like it or not, companies will be able to use machine learning software—driven by quantum computers—to look much more deeply into the mental and emotional stability of their workers.

At the bottom line, Quantum computers are expected to supercharge thousands upon thousands of business applications—machine learning and otherwise—in ways that will marvel, astonish and sometimes give pause. And they appear ready to emerge on the horizon much sooner than you might expect.

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