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Cambridge Quantum Reports Progress toward ‘Meaning Aware’ NLP

UK-based Cambridge Quantum Computing (CQC), a quantum software and algorithm specialist, today released researcher papers on its use of quantum computing to develop intuitive, “meaning-aware” natural language processing (QNLP).

A focal point of artificial intelligence inquiry, NLP that is contextual, that comprehends emotion, nuance, even humor, is NLP’s most advanced and challenging form. In two papers (here and here) posted on the scientific e-print repository arXiv CQC scientists, who employed IBM quantum for their research, discuss conceptual and mathematical foundations for near-term QNLP.

With the aim of “canonically combining linguistic meanings with rich linguistic structure,” including grammar, Professor Bob Coecke (Oxford University) and his QNLP research team worked toward “establishing QNLP as quantum-native, on par with the simulation of quantum systems. Moreover, the leading Noisy Intermediate-Scale Quantum (NISQ) paradigm for encoding classical data on quantum hardware — variational quantum circuits — makes NISQ exceptionally QNLP-friendly,” the company said in its announcement.

“This is the first evidence that NLP is quantum native, meaning this is something that quantum computers can do well, and possibly better than classical methods in the long-term,” said Ilyas Khan, CEO of Cambridge Quantum. “We believe this is one of the most important foundational papers published in the NISQ era and establishes the fact that NLP is finally possible in a meaning-aware manner.”

source: IBM

In the experimental paper (that accompanies the foundational paper) CQC describes how it performed what the company said was the first implementation of an NLP task run on two IBM quantum computers, which CQC has access to as a hub in the IBM Quantum Network.

“Sentences are instantiated as parameterised quantum circuits, and word-meanings are encoded in quantum states,” the company said. “CQC’s scientists explicitly account for grammatical structure, which even in mainstream NLP is not commonplace, by faithfully hard-wiring it as entangling operations. This makes CQC’s approach to QNLP particularly NISQ-friendly. This novel QNLP model shows concrete promise for scalability as the quality of quantum hardware improves.”

“CQC’s work on (QNLP) is a very encouraging example of one of our partners using access to IBM’s quantum systems to push the boundaries of quantum information processing toward new and important applications,” said Dr. Anthony Annunziata, Director of the IBM Quantum Network.

CQC said earlier research by its team achieved a quantum speed-up for QNLP tasks and demonstrated potential quantum advantage for NLP. This was done by algorithmic speed-up for search-related or classification tasks, by utilizing exponentially large quantum state spaces that accommodate complex linguistic structures, and by “novel models of meaning, employing density matrices,” according to the company.

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