  Recent hype surrounding the increasing sophistication of language processing
models has renewed optimism regarding machines achieving a human-like command
of natural language. Research in the area of natural language understanding
(NLU) in artificial intelligence claims to have been making great strides in
this area, however, the lack of conceptual clarity/consistency in how
'understanding' is used in this and other disciplines makes it difficult to
discern how close we actually are. In this interdisciplinary research thesis, I
integrate insights from cognitive science/psychology, philosophy of mind, and
cognitive linguistics, and evaluate it against a critical review of current
approaches in NLU to explore the basic requirements--and remaining
challenges--for developing artificially intelligent systems with human-like
capacities for language use and comprehension.
