Show Notes
We talk about AI generated art with Charlie Snell, a Berkeley student who wrote extensively about AI art for ML@Berkeley's blog (https://ml.berkeley.edu/blog/). We look at multiple slides with art throughout our conversation, so I highly recommend watching the video (https://www.youtube.com/watch?v=gcwidpxeAHI).
In the first part we go through Charlie's explanations of DALL-E, a model trained end-to-end by OpenAI to generate images from prompts. We then talk about CLIP + VQGAN, where CLIP is another model by OpenAI matching prompts and images, and VQGAN is a state-of-the art GAN used extensively in the AI Art scene. At the end of the video we look at different pieces of art made using CLIP, including tricks for using VQGAN with CLIP, videos, and the latest CLIP-guided diffusion architecture. At the end of our chat we talk about scaling laws and how progress in art relates to other advances in ML.
More from The Inside View
Owain Evans is an AI Alignment researcher, research associate at the Center of Human Compatible AI at UC Berkeley, and now leading a new AI safety research group.
This is a special crosspost episode where Adam Gleave is interviewed by Nathan Labenz from the Cognitive Revolution. At the end I also have a discussion with Nathan Labenz about his takes on AI.
Ethan Perez is a Research Scientist at Anthropic, where he leads a team working on developing model organisms of misalignment.
Emil is the co-founder of palette.fm (colorizing B&W pictures with generative AI) and was previously working in deep learning for Google Arts & Culture.
Evan Hubinger leads the Alignment stress-testing at Anthropic and recently published "Sleeper Agents: Training Deceptive LLMs That Persist Through Safety Training".