Natural Language, AI, and Quantum Computing in 2024: Research Ingredients and Directions in QNLP

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.