In addition to sharing IBM’s latest quantum computing news at a CES 2020 session, IBM research director Dario Gil described the business challenges of the quantum decade.
Gil talked with Andreas Hintennach, Ph.D., from Daimler AG, and Vijay Swarup, Ph.D., ExxonMobil, about how industries are redefining the meaning of success in the age of climate change risks and quantum computing opportunities.
Earlier in the presentation, Jeanette Garcia of IBM said that one promise of quantum computing is to make quantum chemistry easier to understand.
Garcia is the senior manager for quantum applications algorithms and theory and her research focus is batteries. She said that the precise nature of quantum computing could make the commercialization process much quicker.
“Quantum algorithms scale polynomially with size—this means we can achieve highly accurate calculations by using much less compute,” she said. “Much less compute means much less time, which means much less money.”
Gil said that this is the most fundamental concept to understand about the advances quantum computing offers.
“There are problems that we’ve put under the rug because we just couldn’t tackle them, the best we could do was to approximate,” he said. “In this world of quantum chemistry, that equation is changing.”
Hintennach, a senior manager for battery research and technology at Daimler, and Swarup, the vice president of research and development at ExxonMobil, represent two key partners in IBM’s Q Network.
The three tech leaders explained the other two big challenges of the quantum decade: How to redefine business success and how to find new ways to collaborate across industries.
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New vector of success
Gil said IBM, Daimler, and ExxonMobil understand there’s a fundamental difference in the nature of the next decade’s challenges.
“The decade ahead is not about turning the crank 10 more times,” he said. “Whether it’s
electrification or de-carbonization or quantum computing as a core paradigm, you’ve got to retool the company and do a lot of other things to change the vector particularly at the scale at which we all operate.”
Hintennach said that for 130 years, innovation in the auto industry meant optimizing the internal combustion engine. Electrification and battery management have made that goal obsolete.
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“Essentially, an old mechanical industry flips into an electrical company,” he said. “Battery management system flips our company to a software company enabling new tech like sensors and energy conversion.”
Swarup said that advanced technology is the solution to the new challenge his industry is facing: How to deliver the energy people want while lowering carbon dioxide emissions.
He said that although computational advances over the last several decades have been the key to most advances in the energy industry, the industry is hitting the limits of traditional computing.
Swarup said that ExxonMobil is relying on a strong internal team of technical experts, collaborations with energy centers and universities around the world, and partners to advance the science at scale.
“Disruption requires collaboration,” he said.
Collaboration as a competitive advantage
Vijay said that ExxonMobil’s biofuels work has been improved by two adjacent technologies: gene editing and faster genome sequencing. These two advances have made the trial and error of ExxonMobil’s work go faster.
“The faster and more accurately you can sequence genomes, the faster you get the organism to produce the hydrocarbons you need to move the trucks and the airplanes,” he said. “Speed and accuracy could take us to the next level.”
Hintennach said that just as the energy sector needs biology researchers, the auto industry needs quantum computing experts and that industries will establish new ways to collaborate over the next two decades.
“We cannot do the OS of a quantum computer or the hardware research, so collaboration is a way to speed things up,” he said.
Gil said that he sees the most potential in the combined power of neurons, qubits, and bits, even as researchers in artificial intelligence, quantum computing, and classical computing make significant advances separately.
“Imagine what is going to happen when there is convergence of all three, when we have computational architecture that brings the best of bits and neurons and qubits,” he said. “Things that have taken us literally decades we will be able to do in years.”