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Cambridge Quantum Computing (CQC) hiring Stephen Clark as head of AI last week could be a sign the company is boosting research into ways quantum computing could be used for natural language processing.

Quantum computing is still in its infancy but promises such significant results that dozens of companies are pursuing new quantum architectures. Researchers at technology giants such as IBM, Google, and Honeywell are making measured progress on demonstrating quantum supremacy for narrowly defined problems. Quantum computers with 50-100 qubits may be able to perform tasks that surpass the capabilities of today’s classical digital computers, “but noise in quantum gates will limit the size of quantum circuits that can be executed reliably,” California Institute of Technology theoretical physics professor John Preskill wrote in a recent paper. “We may feel confident that quantum technology will have a substantial impact on society in the decades ahead, but we cannot be nearly so confident about the commercial potential of quantum technology in the near term, say the next 5 to 10 years.”

CQC has been selling software focused on specific use cases, such as in cybersecurity and pharmaceutical and drug delivery, as the hardware becomes available. “We are very different from the other quantum software companies that we are aware of, which are primarily focused on consulting-based revenues,” CQC CEO Ilyas Khan told VentureBeat.

For example, amid concerns that improvements in quantum hardware will make it easier to break existing algorithms used in modern cryptography, CQC devised a method to generate quantum-resistant cryptographic keys that cannot be cracked by today’s methods. CQC partners with pharmaceutical and drug discovery companies to develop quantum algorithms for improving material discovery, such as working with Roche on drug development, Total on new materials for carbon capture and storage solutions, and CrownBio for novel cancer treatment biomarker discovery.

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Moving into AI

The addition of Clark to CQC’s team signals the company will be shifting some of its research and development efforts toward quantum natural language processing (QNLP). Humans are good at composing meanings, but this process is not well understood. Recent research established that quantum computers, even with their current limitations, could learn to reason with the uncertainty that is part of real-world scenarios.

“We do not know how we compose meaning, and therefore we have not been sure how this process can be carried over to machines/computers,” Khan said.

QNLP could enable grammar-aware representation of language that makes sense of text at a deeper level than is currently available with state-of-the-art NLP algorithms like Bert and GPT 3.0. The company has already demonstrated some early success in representing and processing text using quantum computers, suggesting that QNLP is within reach.

Clark was previously senior staff research scientist at DeepMind and led a team working on grounded language learning in virtual environments. He has a long history with CQC chief scientist Bob Coecke, with whom he collaborated 15 years ago to devise a novel approach for processing language. That research stalled due to the limitations of classical computers. Quantum computing could help address these bottlenecks, and there are plans to continue that research program, Clark said in a statement.

“The methods we developed to demonstrate this could improve a broad range of applications where reasoning in complex systems and quantifying uncertainty are crucial, including medical diagnoses, fault-detection in mission-critical machines, and financial forecasting for investment management,” Khan said.

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