Diffusion Models Live Event
lewtun, johnowhitaker
We are excited to share that the [Diffusion Models Class](https://github.com/huggingface/diffusion-models-class) with Hugging Face and Jonathan Whitaker will be **released on November 28th** 🥳! In this free course, you will learn all about the theory and application of diffusion models -- one of the most exciting developments in deep learning this year. If you've never heard of diffusion models, here's a demo to give you a taste of what they can do:

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To go with this release, we are organising a **live community event on November 30th** to which you are invited! The program includes exciting talks from the creators of Stable Diffusion, researchers at Stability AI and Meta, and more!

To register, please fill out [this form](http://eepurl.com/icSzXv). More details on the speakers and talks are provided below.

## Live Talks

The talks will focus on a high-level presentation of diffusion models and the tools we can use to build applications with them.

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        <p><strong>David Ha: <em>Collective Intelligence and Creative AI</em></strong></p>
        <p>David Ha is the Head of Strategy at Stability AI. He previously worked as a Research Scientist at Google, working in the Brain team in Japan. His research interests include complex systems, self-organization, and creative 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.</p>
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        <p><strong>Devi Parikh: <em>Make-A-Video: Diffusion Models for Text-to-Video Generation without Text-Video Data</em></strong></p>
        <p>Devi Parikh is a Research Director at the Fundamental AI Research (FAIR) lab at Meta, and an Associate Professor in 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.</p>
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        <p><strong>Patrick Esser: <em>Food for Diffusion</em></strong></p>
        <p>Patrick Esser is a Principal Research Scientist at Runway, leading applied research efforts including the core model behind Stable Diffusion, otherwise known as High-Resolution Image Synthesis with Latent Diffusion Models.</p>
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        <p><strong>Justin Pinkney: <em>Beyond text - giving Stable Diffusion new abilities</em></strong></p>
        <p>Justin is a Senior Machine Learning Researcher at Lambda Labs working on image generation and editing, particularly for artistic and creative applications. He loves to play and tweak pre-trained models to add new capabilities to them, and is probably best known for models like: Toonify, Stable Diffusion Image Variations, and Text-to-Pokemon.</p>
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        <p><strong>Apolinário Passos: <em>DALL-E 2 is cool but... what will come after the generative media hype?</em></strong></p>
        <p>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.</p>
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