Nina Beguš, CompLit PhD ’20, now a postdoctoral researcher at the University of California (UC), Berkeley’s Center for Science, Technology, Medicine, and Society […]. As AI becomes ever more interwoven in daily life—perhaps faster than any technology in human history—Beguš says it’s critical to get a better understanding of AI’s “latent space,” the hidden mathematical area that processes information and eventually produces an output.
In a new paper for Antikythera: Journal for the Philosophy of Planetary Computation, a peer-reviewed journal published in parallel with the Antikythera book series by MIT Press, Nina and Gašper Beguš, PhD ’18, director of UC Berkeley’s Speech and Computation Lab, partnering with the artist collective Metahaven, begin to map out this space. Using general adversarial networks (GANs), a type of AI that poses two neural networks against one another to produce data, and James Joyce’s notoriously difficult novel, Finnegans Wake, the authors were able to get a picture of AI in the process of learning. They showed, as Nina Beguš describes in the interview below, that GANs acquire language much like humans do.
Founded as a graduate program in 1904 and joining with the undergraduate Literature Concentration in 2007, Harvard’s Department of Comparative Literature operates at the crossroads of multilingualism, literary study, and media history.
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