​About the AI Research Circle

​The AI Research Circle is a community gathering at The Commons where we explore and discuss AI research papers together. You don’t need to be a researcher—just bring curiosity and an interest in the field.

​Each session, we choose a paper, break it down into plain language, and dive into open conversation. The goal is to make cutting-edge ideas accessible, spark thoughtful debate, and connect across disciplines.

​Session Details

​Diffusion models have transformed generative AI, powering breakthroughs from image synthesis to text-to-3D. But it all started with one landmark paper: Denoising Diffusion Probabilistic Models (Ho et al., 2020). https://arxiv.org/abs/2006.11239

​In this session, we’ll dive into this foundational work—the paper that kicked off the modern wave of diffusion research. Together, we’ll:

• ​Unpack the basics: how diffusion models gradually add noise to data and then learn to reverse the process.

• ​Discuss key results and insights: why this method worked so well compared to GANs and VAEs.

• ​Connect to the present: how later innovations like Latent Diffusion and Consistency Models build on these ideas.

• ​Open the floor: discussion and Q&A for all levels, from newcomers to researchers.

​Reading

​Please read: Denoising Diffusion Probabilistic Models (Ho, Jain, Abbeel, 2020). arXiv link

​Who should join

​Anyone interested in AI and generative models. No prior expertise required—we’ll balance intuition and accessibility with enough technical detail to keep things engaging.

​Additional Resources (Optional)

​https://github.com/diff-usion/Awesome-Diffusion-Models
Qwen-Image Technical Report: https://arxiv.org/abs/2508.02324