Natural Language, AI, and Quantum Computing in 2024: Research
  Ingredients and Directions in QNLP
Dominic Widdows Willie Aboumrad Dohun Kim Sayonee Ray Jonathan Mei
Language processing is at the heart of current developments in artificial
intelligence, and quantum computers are becoming available at the same time.
This has led to great interest in quantum natural language processing, and
several early proposals and experiments. This paper surveys the state of this
area, showing how NLP-related techniques including word embeddings, sequential
models, attention, and grammatical parsing have been used in quantum language
processing. We introduce a new quantum design for the basic task of text
encoding (representing a string of characters in memory), which has not been
addressed in detail before.
  As well as motivating new technologies, quantum theory has made key
contributions to the challenging questions of 'What is uncertainty?' and 'What
is intelligence?' As these questions are taking on fresh urgency with
artificial systems, the paper also considers some of the ways facts are
conceptualized and presented in language. In particular, we argue that the
problem of 'hallucinations' arises through a basic misunderstanding: language
expresses any number of plausible hypotheses, only a few of which become
actual, a distinction that is ignored in classical mechanics, but present
(albeit confusing) in quantum mechanics.