We’re excited to share that the Diffusion Models Class with Hugging Face and Jonathan Whitaker shall be released on November twenty eighth 🥳! On this free course, you’ll learn all in regards to the theory and application of diffusion models — some of the exciting developments in deep learning this yr. Should you’ve never heard of diffusion models, here’s a demo to present you a taste of what they will do:
To go along with this release, we’re organising a live community event on November thirtieth to which you might be invited! This system includes exciting talks from the creators of Stable Diffusion, researchers at Stability AI and Meta, and more!
To register, please fill out this type. More details on the speakers and talks are provided below.
Live Talks
The talks will give attention to a high-level presentation of diffusion models and the tools we will use to construct applications with them.
David Ha: Collective Intelligence and Creative AI
David Ha is the Head of Strategy at Stability AI. He previously worked as a Research Scientist at Google, working within the Brain team in Japan. His research interests include complex systems, self-organization, and artistic applications of machine learning. Prior to joining Google, He worked at Goldman Sachs as a Managing Director, where he co-ran the fixed-income trading business in Japan. He obtained undergraduate and masters degrees from the University of Toronto, and a PhD from the University of Tokyo.
Devi Parikh: Make-A-Video: Diffusion Models for Text-to-Video Generation without Text-Video Data
Devi Parikh is a Research Director on the Fundamental AI Research (FAIR) lab at Meta, and an Associate Professor within the School of Interactive Computing at Georgia Tech. She has held visiting positions at Cornell University, University of Texas at Austin, Microsoft Research, MIT, Carnegie Mellon University, and Facebook AI Research. She received her M.S. and Ph.D. degrees from the Electrical and Computer Engineering department at Carnegie Mellon University in 2007 and 2009 respectively. Her research interests are in computer vision, natural language processing, embodied AI, human-AI collaboration, and AI for creativity.
Patrick Esser: Food for Diffusion
Patrick Esser is a Principal Research Scientist at Runway, leading applied research efforts including the core model behind Stable Diffusion, otherwise referred to as High-Resolution Image Synthesis with Latent Diffusion Models.
Justin Pinkney: Beyond text – giving Stable Diffusion latest abilities
Justin is a Senior Machine Learning Researcher at Lambda Labs working on image generation and editing, particularly for artistic and artistic applications. He likes to play and tweak pre-trained models so as to add latest capabilities to them, and might be best known for models like: Toonify, Stable Diffusion Image Variations, and Text-to-Pokemon.
Apolinário Passos: DALL-E 2 is cool but… what is going to come after the generative media hype?
Apolinário Passos is a Machine Learning Art Engineer at Hugging Face and an artist who focuses on generative art and generative media. He founded the platform multimodal.art and the corresponding Twitter account, and works on the organization, aggregation, and platformization of open-source generative media machine learning models.
