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By Shervin Le Du, former student of the Master in Quantum Computing Technology. In this introduction to Quantum Natural Language Processing (QNLP), we will see how words' meaning is classically encoded into computers. We will then discuss the challenges representing the meaning of sentences, and present a framework to achieve it (DisCoCat). After seeing that this method benefits a quantum speedup, we will present three examples of use cases. If you want to know Shervin's work in more detail, you may access the latest version of his master's thesis here: https://arxiv.org/abs/2202.11766. Shervin has studied Natural Language Processing (NLP) at the University of Paris. And currently works in the field of Text-to-Speech, he joined the UPM master with the objective of seeing how quantum computing could apply to NLP. After discovering the growing field of Quantum Natural Language Processing (QNLP), he decided to defend a thesis on this subject. Webinar hosted by Universidad Politécnica de Madrid, as part of its Master in Quantum Computing Technology (https://www.quantum-explore.com)