AQuI Speaker Series: Quantum Natural Language Processing - Mithün Paul

Title: Quantum Natural Language Processing

Abstract: Quantum Natural Language Processing (QNLP) is a very nascent field which deals with using quantum computers to solve natural language processing problems, a sub field of Artificial Intelligence. Quantum advantage for QNLP tasks has already been established in literature and has been attributed to the fact that quantum models for natural language processing canonically incorporate linguistic meanings with rich linguistic structure, most notably grammar. The fact that it takes a quantum-like model to combine meaning and structure, establishes QNLP as quantum-native, on par with simulation of quantum systems. Moreover, the now leading Noisy Intermediate-Scale Quantum (NISQ) paradigm for encoding classical data on quantum hardware, variational quantum circuits, makes NISQ exceptionally QNLP-friendly: linguistic structure can be encoded as a free lunch, in contrast to the apparently exponentially expensive classical encoding of grammar. In this talk, Mithün will talk about quantum algorithms for incorporating compositionality, after providing some basic conceptual foundations in zx calculus and graphical modeling needed to understand QNLP. He will then show how quantum NLP contributes to quantum advantage, some of his own research and end with talking about the state of the art in QNLP.

Bio:
Mithün is a Research Scientist at the Data Science Institute of the University of Arizona. He recently graduated from his PhD from the computer science department of University of Arizona and finished a post-doc at the Information Sciences Institute in California. He got his Masters in Physics along with his undergrad degrees from Birla Institute of Technology and Science(BITS), Pilani, India. His research interests include natural language processing, artificial intelligence, quantum computation and quantum consciousness.