Cambridge Quantum Releases World’s First Toolbox for Library and Processing of Quantum Natural Language Processing

By converting sentences to quantum circuits, ‘lambeq’ accelerates the development of practical QNLP applications such as quantum computing systems scaling

CAMBRIDGE, England, October 13, 2021 / PRNewswire / – Cambridge Quantum (“CQ”) today announced the release of the world’s first toolbox and library for Quantum Natural Language Processing (QNLP). The toolkit is called lambeq, named after the late mathematician and linguist Joachim Lambek.

lambeq is the world’s first software toolbox for QNLP capable of converting sentences into a quantum circuit. It is designed to accelerate the development of practical, real-time QNLP applications, such as automated dialogue, text mining, language translation, text-to-speech, language generation, and bioinformatics.

lambeq has been released on a fully open basis for the benefit of the world quantum computing community and the fast growing ecosystem of quantum computer scientists, developers and users. lambeq works smoothly with CQs TKET, the world’s leading and fastest growing quantum software development platform, also fully open-sourced. This gives QNLP developers access to the widest possible range of quantum computers.

lambeq was conceived, designed and constructed by CQ’s Oxford-based quantum computing team led by Chief Scientist Bob Coecke, with senior researcher Dimitrios Kartsaklis, Ph.D., as chief architect of the platform. lambeq and QNLP more broadly are the result of a research project spanning a decade.

“Our team has been involved in basic work investigating how quantum computers can be used to solve some of the most difficult problems in artificial intelligence,” Coecke said. “This work was based on progress that was originally groundbreaking by me, Steve Clark, now CQ’s Head of AI and others. NLP is the core of these studies. The release of lambeq is the natural next step after its release a few months ago, which provided details of the world’s first QNLP implementation of CQ on actual quantum computers and our first revelation of the basic principles of December 2019. “

“In various articles published over the last year,” Coecke added, “we have not only provided details on how quantum computers can improve NLP, but also demonstrated that QNLP is ‘quantum native’, meaning that the compositional structure of languages ​​is mathematically the same as for quantum systems. This will ultimately move the world away from the current paradigm of AI, which relies on brute force techniques that are opaque and approximate. “

lambeq enables and automates the design and implementation of NLP experiments of the composition distribution (DisCo) type previously described by CQ researchers. This means moving from syntax / grammar charts encoding the structure of a text to either (classical) tensor networks or quantum circuits implemented with TKET, ready to be optimized for machine learning tasks such as text classification. lambeq has a modular design so that users can swap components in and out of the model and have flexibility in architectural design.

lambeq removes barriers to entry for GPs and researchers focused on AI and human-machine interaction, possibly one of the most significant uses of quantum technologies. TKET has gained a worldwide user base now measured in the hundreds of thousands. lambeq has the potential to become the most important toolkit for the quantum computing community seeking to interact with QNLP applications that are among the most important markets for AI. A key point that has become clear recently is that QNLP will also be useful for analyzing symbol sequences that occur in genomics as well as in proteomics.

Merck Group, a launch partner and early adopter of lambeq, recently published a research paper on QNLP as part of a project with the Quantum Entrepreneurship Laboratory innovation program from the Technical University of Munich.

Thomas Ehmer from Merck’s IT Healthcare Innovation Incubator and co-founder of Quantum Computing Interest Group, said: “Using the unique features of quantum computing for fundamental breakthroughs is an important part of our research at Merck. proved that binary classification tasks for sentences using QNLP techniques can achieve results comparable even at this stage with existing classical methods.It is clear that the infrastructure around quantum computation must be advanced before these techniques can be used commercially. we see how the approach used in QNLP opens the way to explainable AI and thus to more precise intelligence that is also responsible – which is critical in medicine. “

“There is a lot of interesting theoretical work on QNLP, but theory is usually at a distance from practice,” Kartsaklis said. “With lambeq, we give researchers the opportunity to gain practical experience with experimental aspects of QNLP, which is currently completely unexplored. This is a crucial step towards reaching the point where practical NLP applications in the real world of quantum hardware become a reality.”

lambeq has been released as a conventional Python repository on GitHub and is available here: https://github.com/CQCL/lambeq. The quantum circuits generated by lambeq have so far been executed and implemented on IBM quantum computers and Honeywell Quantum Solutions’ H series devices.

The toolkit is introduced by a technical report uploaded on arxiv available here: https://arxiv.org/abs/2110.04236. A more generally accessible blog post can be found here: https://medium.com/cambridge-quantum-computing/quantum-natural-language-processing-ii-6b6a44b319b2. Technical inquiries can be directed to lambeq-support@cambridgequantum.com.

In recent years, NLP-based applications have become ubiquitous across sectors worldwide, from customer service and consumer technology to healthcare and advertising. According to industry analysts, the global NLP market is expected to be worthwhile $ 127.26 billion in 2028 with a CAGR of almost 30 percent[1].

About Cambridge Quantum

Founded in 2014 and supported by some of the world’s leading quantum computing companies, CQ is a global leader in quantum software and quantum algorithms, enabling customers to get the most out of rapidly evolving quantum computing hardware. CQ has offices in Europe, the USA and Japan. On June 8, 2021, CQ announced a merger with Honeywell Quantum Solutions, which is expected to close in Q4 2021.

For more information, visit CQ at http://www.cambridgequantum.com and on LinkedIn. Access the source code for lambeq, TKET, Python bindings and utilities at GitHub.

[1] https://www.fortunebusinessinsights.com/industry-reports/natural-language-processing-nlp-market-101933

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