Cambridge Quantum Releases Natural Language Processing Toolkit and Library
Cambridge Quantum ;today released lambeq, a toolkit and library for quantum natural language processing (QNLP). The toolkit is named after the late mathematician and linguist Joachim Lambek.
lambeq is a software toolkit for QNLP capable of converting sentences into quantum circuits. It is designed to accelerate the development of practical, real-world QNLP applications, such as automated dialogue, text mining, language translation, text-to-speech, language generation, and bioinformatics.
lambeq has been released as open-source software and works seamlessly with the CQ TKET quantum software development platform.
"Our team has been involved in foundational work that explores how quantum computers can be used to solve some of the most intractable problems in artificial intelligence," said CQ's Oxford-based quantum computing research team leader and chief scientist, Bob Coecke, in a statement.
"In various papers published over the course of the past year," Coecke added, "we have not only provided details on how quantum computers can enhance NLP but also demonstrated that QNLP is quantum native, meaning the compositional structure governing language is mathematically the same as that governing quantum systems. This will ultimately move the world away from the current paradigm of AI that relies on brute force techniques that are opaque and approximate."
lambeq enables and automates the design and deployment of NLP experiments of the compositional-distributional (DisCo) type. This means moving from syntax/grammar diagrams, which encode a text's structure, 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.
Merck Group was a launch partner and early adopter of lambeq. Thomas Ehmer from Merck's IT Healthcare Innovation Incubator and co-founder of the Quantum Computing Interest Group, said, "Using the unique features of quantum computing for fundamental breakthroughs is an important part of our research at Merck. Our recently disclosed project in QNLP with researchers from TU Munich has proven that binary classification tasks for sentences using QNLP techniques can achieve results comparable even at this stage to existing classical methods. Clearly, the infrastructure around quantum computing will need to advance before these techniques can be employed commercially. Critically, we can see how the approach employed in QNLP opens the route toward explainable AI, and thus to more accurate intelligence that is also accountable, which is critical in medicine."
"There is a lot of interesting theoretical work on QNLP, but theory usually stands at some distance from practice," said senior scientist Dimitrios Kartsaklis, chief architect of the platform, in a statement. "With lambeq, we give researchers the opportunity to gain hands-on experience on experimental aspects of QNLP, which is currently completely unexplored ground. This is a crucial step toward reaching the point where practical, real-world NLP applications on quantum hardware become a reality."
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 Fortune Business Insights, the global NLP market is expected to be worth $127.26 billion by 2028, growing at a compound annual rate of nearly 30 percent.