(PRNewswire) Cambridge Quantum Computing (CQC) has announced the publication of a research paper on the online pre-print repository arxiv (available here) that provides details of the largest ever experimental implementation of Natural Language Processing (NLP) tasks on a quantum computer.
Titled “QNLP in Practice: Running Compositional Models of Meaning on a Quantum Computer,” the paper presents the first “medium-scale” implementation of common NLP tasks. Completed on an IBM quantum computer, the experiment, which instantiated sentences as parameterised quantum circuits, embeds word meanings as quantum states which are “entangled” according to the grammatical structure of the sentence.
The paper builds on prior proof-of-concept work (see here for the previous experiment) and, significantly, achieves convergence for the far larger datasets that are employed here. One of the objectives of the CQC team is to describe Quantum Natural Language Processing (QNLP) and their results in a way that is accessible to NLP researchers and practitioners thus paving the way for the NLP community to engage with a quantum encoding of language processing.
Bob Coecke, CQC’s Chief Scientist and also the Head of CQC’s QNLP project, commented, “We are working on an immensely ambitious project at CQC that is aimed at utilising quantum computers, as they scale, to move beyond expensive black-box mechanisms for NLP to a paradigm where we become more effective, more accurate and more scalable in an area of computer science that epitomises artificial intelligence. Having made considerable progress already on our ‘quantum-native’ brand of compositional NLP, we are now moving beyond our initial research and working on applications that can be developed in synch with timelines provided by quantum computing hardware companies such as IBM, Honeywell, Google and others.”