The Gradient: Perspectives on AI
In episode 83 of The Gradient Podcast, Daniel Bashir speaks to Peli Grietzer.
Peli is a scholar whose work borrows mathematical ideas from machine learning theory to think through “ambient” and ineffable phenomena like moods, vibes, cultural logics, and structures of feeling. He is working on a book titled Big Mood: A Transcendental-Computational Essay in Art and contributes to the experimental literature collective Gauss PDF. Peli has a PhD in mathematically informed literary theory from Harvard Comparative Literature in collaboration with the HUJI Einstein Institute of Mathematics.
Have suggestions for future podcast guests (or other feedback)? Let us know here or reach us at [email protected]
Subscribe to The Gradient Podcast: Apple Podcasts | Spotify | Pocket Casts | RSSFollow The Gradient on Twitter
Outline:
* (00:00) Intro
* (02:17) Peli’s background
* (10:40) Daniel takes 2 entire minutes to ask how Peli thinks about ~ Art ~
* (26:10) Idealism and art as revealing the nature of reality, extralinguistic experiences of truth through literature
* (52:05) The autoencoder as a way to understand Romantic theories of art
* (1:14:55) More on how Peli thinks about autoencoders
* (1:18:05) Connections to ambient meaning, stimmung/mood
* (1:37:18) Examples of poetry/literature as mathematical experience, aesthetic unity and totalizing worldviews
* (1:51:15) Moods clashing within a single work
* (2:10:14) Modernist writers
* (2:32:46) Outro
Links:
* Peli’s Twitter
* Why poetry is a variety of mathematical experience
* Peli’s thesis