-- Converting sentences into quantum circuits, 'lambeq' accelerates the 
development of practical QNLP applications as quantum computing systems scale


Cambridge Quantum (https://cambridgequantum.com/ ) ("CQ") today announced the 
release of the world's first toolkit 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 toolkit for QNLP capable of converting 
sentences into a quantum circuit. 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 on a fully open-sourced basis for the benefit of the 
world's quantum computing community and the rapidly growing ecosystem of 
quantum computing researchers, developers and users. lambeq works seamlessly 
with CQ's TKET ( 
https://cambridgequantum.com/cambridge-quantums-tket-is-now-open-sourced/ ), 
the world's leading and fastest-growing quantum software development platform 
that is also fully open-sourced. This provides QNLP developers with access to 
the broadest possible range of quantum computers. 

lambeq was conceived, designed and engineered by CQ's Oxford-based quantum 
computing research team led by Chief Scientist Bob Coecke, with senior 
scientist Dimitrios Kartsaklis, Ph.D., as chief architect of the platform. 
lambeq, and QNLP more broadly, is the result of a research project stretching 
back over a decade.

"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 Coecke. "This work was based on advances 
originally pioneered by me, Steve Clark, now CQ's Head of AI, and others. NLP 
sits at the heart of these investigations. The release of lambeq is the natural 
next step after the publication a few months ago that provided details of the 
world's first QNLP implementation by CQ on actual quantum computers, and our 
initial disclosure of the foundational principles in December 2019."

"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 that CQ scientists have 
previously described. 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 optimised 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 
architecture design.

lambeq removes the barriers to entry for practitioners and researchers who are 
focused on AI and human-machine interactions, potentially one of the most 
significant applications 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 engage with QNLP applications that are amongst the most important 
markets for AI. A key point that has become apparent recently is that QNLP will 
also be applicable to the analysis of symbol sequences that arise 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 innovation programme 
Quantum Entrepreneurship Laboratory from the Technical University of Munich. 

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 
towards 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 Kartsaklis. "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 towards reaching the point where practical, real-world NLP applications on 
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 thus 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 enquiries 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 worth $127.26 billion by 2028 with a CAGR of nearly 30 percent[1].

About Cambridge Quantum
Founded in 2014 and backed by some of the world's leading quantum computing 
companies, CQ is a global leader in quantum software and quantum algorithms, 
enabling clients to achieve the most out of rapidly evolving quantum computing 
hardware. CQ has offices in Europe, USA, and Japan. On 8th June 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 (https://www.linkedin.com/company/21661539/ ). Access the source code 
for lambeq, TKET, Python bindings and utilities on GitHub 
(https://github.com/CQCL ).

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


SOURCE  Cambridge Quantum