
Machine Learning at Berkeley
237 posts

Machine Learning at Berkeley
@BerkeleyML
Students at UC Berkeley working on academic research, ML education, industry projects, and fostering a vibrant ML community 🧠💡






“Hop” over to our theater on Sunday, March 22 to earn how story and animation inform each other to create the world of of Disney and Pixar’s latest feature film, "Hoppers" (2026), with Pixar’s Margaret Spencer, John Cody Kim, James W. Brown, and Cody Lyon. bit.ly/4l6kXaC


We're excited to announce the second Berkeley BioML seminar of the semester happening next Tuesday 2/17! Join us for a talk by Kenny Workman (@kenbwork) from LatchBio about the performance of agents for spatial biology analysis. luma.com/f3xa3dst


I had a fun time writing a deep dive on Diffusion Language Models - with an equation walkthrough and Excalidraw sketches ✏️ In Part 1, I focused on the method: what does “noise” even mean for text, and how do DLMs denoise back into tokens? winterrykim.github.io/blog/2026/dlm-…




At the Berkeley BioML Seminar next Monday, 11/17, we'll be hearing from @chengzhong_ye about GPN-Star, a phylogenetically-aware genomic language model that achieves state-of-the-art accuracy on a diverse range of downstream tasks. Sign up here! luma.com/foy5xsu0



Training our advisors was too hard, so we tried to train black-box models like GPT-5 instead. Check out our work: Advisor Models, a training framework that adapts frontier models behind an API to your specific environment, users, or tasks using a smaller, advisor model (1/n)!
