Lingthusiasm - A Podcast That's Enthusiastic About Linguistics

When a human learns a new word, we're learning to attach that word to a set of concepts in the real world. When a computer "learns" a new word, it is creating some associations between that word and other words it has seen before, which can sometimes give it the appearance of understanding, but it doesn't have that real-world grounding, which can sometimes lead to spectacular failures: hilariously implausible from a human perspective, just as plausible from the computer's. In this episode, your host Lauren Gawne gets enthusiastic about how computers process language with Dr. Emily M. Bender, who is a linguistics professor at the University of Washington, USA, and cohost of the podcast Mystery AI Hype Theater 3000. We talk about Emily's work trying to formulate a list of rules that a computer can use to generate grammatical sentences in a language, the differences between that and training a computer to generate sentences using the statistical likelihood of what comes next based on all the other sentences, a