Researchers show that quantum computers can reason

Like humans, quantum computers can make decisions even in the face of incomplete data and uncertainty.

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Quantum computers can learn to reason, even when burdened with uncertainty and incomplete data, concludes a team of scientists from U.K.-based quantum software developer Cambridge Quantum Computing (CQC).

This ability is similar to intuitive human reasoning, which allows people to draw conclusions and make decisions despite a lack of comprehensive information. CQC’s research confirms a belief among many scientists that quantum computers have a natural propensity for reasoning.

In a paper published on the open-access scholarly archive arXiv, CQC scientists detail how they developed methods that demonstrated how quantum machines can learn to infer hidden information from general probabilistic reasoning models. If replicable, these methods could improve a broad range of applications for quantum computing, including medical diagnoses, fault-detection in mission-critical machines, and financial forecasting for investment management.

Classical computers are capable of assisting with some reasoning tasks, but they require excessive amounts of time-consuming computations, data, power, and gratuitous praise. And for all that trouble, classical computers still “cannot offer simple explanations for their answers and struggle when asked how confident they are on certain possible outcomes,” CQC team member Matthias Rosenkranz writes in Medium. “These issues become particularly severe when a decision is the result of multiple yes/no outcomes.”

Admittedly, it’s not like you can run down to Best Buy today and purchase a quantum computer. They are not yet ubiquitous. IBM apparently is collecting quantum computers the way Jerry Seinfeld collects classic and rare cars. Big Blue also is installing a quantum computer at Cleveland Clinic, the first private-sector recipient of an IBM Quantum System One.

But quantum computing’s time in the sun inches inexorably closer.

“Quantum computing (QC) proof of concept (POC) projects abound in 2021 with commercialization already happening in pilots and building to broader adoption before 2025,” REDDS Capital Chairman and General Partner Stephen Ibaraki writes in Forbes. “In my daily engagements’ pro bono with global communities – CEOs, computing science/engineering organizations, United Nations, investments, innovation hubs – I am finding nearly 50% of businesses see applications for QC in five years, though most don’t fully understand how this will come about.”

IBM has not been the only major tech company developing quantum computing technology. Google announced in 2019 it had designed a machine that achieved quantum supremacy, able to compute in 200 seconds what the company estimates would take 10,000 years for a classical computer. Amazon, Intel, Honeywell, Microsoft, and many other vendors (along with the nation of China) are trying to ride the QC train.

One thing all of them are dealing with is that quantum computers don’t use the same type of logic as classical computers. This requires changes in how code needed for them to run them is written. The CQC team created two algorithms that enable variational inference (a method from machine learning that approximates probability densities in quantum computers).

Ibaraki expects “proven commercialization” of quantum computing within a decade. Industries most likely to roll out commercial quantum computing deployments are the ones leading the way in POCs: artificial intelligence and machine learning, financial services, healthcare, IT, material science, energy, science, and transportation/logistics.

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