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AWS, QCI look to bridge classical and quantum computing

Quantum computing startup QCI has developed a SaaS-based offering for AWS' cloud platform in hopes of bringing classical and quantum computing platforms closer together.

Hoping to bridge the gap between classical and quantum computers, startup Quantum Computing Inc.'s Qatalyst constrained optimization technology now works with AWS across the two platforms.

The offering permits inexperienced quantum users to submit complex problems to one of several quantum-based systems through AWS' Braket quantum-based service. Users have the option of submitting the same problem to Qatalyst for either hybrid classical/quantum or can submit it to Qatalyst for pure quantum processing.

"Our goal from the start was focusing on bringing business value to users and to provide them with a software product that is agnostic across quantum computing platforms," said Robert Liscouski, CEO of QCI. "We also want to reduce the amount of dependency there is on high-level programming resources that, historically, are required to run a quantum computer."

QCI is focusing on organizations that are looking to solve a range of complex problems across multiple industries. The goal, at least over the short term, is to get users to test out the technology to prove it can make a meaningful difference in their production environments.

"I'd love to generate revenues, but my driver is really getting people to use the technology and generate some use cases to demonstrate the validity and ease of use of the approach to the technology," Liscouski said. "The types of problems we are working on range from supply chain to logistics to pharma looking at drug repurposing, but within the context of constrained optimization."

Quantum computing systems compared to classical computing
Quantum computing differs from classical computing systems in ways that allow quantum systems to crunch data exponentially faster and with added security.

One barrier to IT pros even wanting to experiment with quantum computing is the lack of in-house expertise in the technology and no clear vision of what the return on investment will be in what they might see as an unproven technology.

Liscouski believes he has a way around that barrier by making first contact with the business side of the house -- not the technical side -- to convince businesspeople he has an answer to a problem they are trying to solve. Over the past year, he added, these conversations have been easier to have because the business side is more knowledgeable about quantum technologies and see more clearly how it resolves longtime problems.

One analyst thinks approaching business people first can be the most fruitful approach. Although technically inexperienced, an increasingly number of businesspeople have become aware of what quantum computing can offer their operations.

Where we are with quantum is where we were with AI 10 years ago. If you think quantum will make a difference, my advice is to get in now.
Matthew BrisseResearch vice president, Gartner

"Customers I talk to are not the researchers, they are on the business side asking, 'Is there a competitive differentiation I'm missing out on?' or 'Is it too early or even too late to get in?'" said Matthew Brisse, research vice president at Gartner. "Where we are with quantum is where we were with AI 10 years ago. If you think quantum will make a difference, my advice is to get in now," he said.

Other observers have said buying into a hybrid strategy like AWS' can be a sensible first step toward quantum computing. Those users should be ready to use quantum systems as coprocessors to classical systems for some time to come.

"It would be worthwhile for end users to try out both to see which one solves our problem the best," said Doug Finke, managing editor of the Quantum Computer Report and longtime executive at a number of high-tech firms, including Intel and Western Digital. "But quantum systems power isn't enough to do better than classical computers. There are some very good classical algorithms that solve many complex problems."

AWS officials agree that early efforts of bridging classical and quantum platforms are a good step, but it will a long time before a Goldilocks balance is struck in deciding between either platform.

"As time goes by and quantum hardware becomes more powerful, then it might take center stage in certain application areas," said Richard Moulds, general manager at Amazon Braket. "But right now, we're in this era of hybrid [quantum and classical] compute models with a lot of research going on as to how these two different approaches can be combined most effectively."

AWS has plenty of company in quantum-based services for the enterprise. Microsoft has previewed its cloud-based quantum service, which allows users to access quantum capabilities of its hardware partners, including IonQ and Honeywell. IBM too, plans by 2023 to make multiple families of prebuilt runtimes callable from cloud-based APIs to deliver quantum services for addressing industry-specific problems.

Through AWS Braket, users have access to quantum systems using different technologies, including IonQ (ion trap), D-Wave (quantum annealing) and Rigetti (superconducting chips), as well as toolkits to develop applications for each of those systems.

Besides offering access to AWS' classical and quantum computing resources, QCI's QikStart program, which rolled out in February, provides users with access to Qatalyst quantum application accelerator, expert resources and funding to explore new more practical products that would be ready for production environments.

AWS provides simulators bundled into its Braket SDK free of charge. This makes it more convenient for users to access and to debug their quantum circuits, Moulds said. They can then run them on larger-scale simulators on the service and ultimately run them on quantum hardware. AWS currently supports two simulators, state vector and tensor network up to 50 qubits.

"This is all part of the lifecycle of how customers manage experiments," Amazon Braket's Moulds said. "When you take this approach, it can be done simply and cheaply before you move onto the [quantum] hardware to get your final results."

As editor at large with TechTarget's News Group, Ed Scannell is responsible for writing and reporting breaking news, news analysis and features focused on technology issues and trends affecting corporate IT professionals. He has also worked for 26 years at Infoworld and Computerworld covering enterprise class products and technologies from larger IT companies, including IBM and Microsoft, as well as serving as editor of Redmond for three years overseeing that magazine's editorial content.

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