This is Part I of our Deep Learning Series where Le Random's editor-in-chief Peter Bauman (Monk Antony) speaks with the most relevant figures in deep learning art. In this first installment, Peter speaks with two of the earliest artists to engage with the intersection of art and deep generative models, Tom White (dribnet) and Gene Kogan.

They explore the artistic, philosophical and cultural implications of GANs and deep generative models, drawing on the artists' early experiences and perspectives in the field . The conversation touches on the origins of their interest in GANs, the evolution of AI and its perception, critiques of AI art, the nature of machine representations, and the connection between AI and decentralization.

Chapters 📖:

[00:00:00]: Introduction and Guest Overview[00:01:50]: First Encounters with GANs and Initial Excitement[00:04:04]: Gene's Journey with Machine Learning and Art[00:08:55]: The Rise of AI Twitter and Deep Learning Culture[00:12:04]: The Mission to Make AI Tools Accessible[00:17:56]: Changing Philosophies of Computation[00:21:54]: Critiques of AI in the Art World[00:27:42]: Tom's Algorithmic Gaze, Machine Perception & The Platonic Representation Hypothesis[00:34:00]: Art by AI for AI—Tom's Machine Representation & Phil's Hypothesis[00:37:49]: Decentralized AI and its Evolution[00:40:33]: Tom's Early Work at MIT and Interactive Graphics[00:43:13]: Final Thoughts