The Principles of Diffusion Models by Lai et al.: thoughts on the monograph [D]

<!-- SC_OFF --><div class="md"><p>Peter Holderrieth and Ezra Erives just released their new MIT 2026 course on flow matching and diffusion models! It introduces the full stack of

<!-- SC_OFF --><div class="md"><p>&#x200b;</p> <p>## Abstract</p> <p>Post-training makes language models more decisive without necessarily making them more accurate — and we find

<!-- SC_OFF --><div class="md"><p>Sorry in advance, these might be bad questions, as I don't have any interviews right now and thus no specific questions, but I'm trying to get a

<a href="https://news.ycombinator.com/item?id=48040002">Comments</a>

<!-- SC_OFF --><div class="md"><p><strong>Noam Brown</strong> — OpenAI Research Scientist and co-creator of o1, Libratus, and Cicero — sat down with Dwarkesh Patel for a 1h 20m

<!-- SC_OFF --><div class="md"><p>If the claims presented in the paper are true, this will be very big for multi-user local inference</p> </div><!-- SC_ON --> &#32; submitted by

&#32; submitted by &#32; <a href="https://www.reddit.com/user/nnxnnx"> /u/nnxnnx </a> <br /> <span><a href="https://introspective-diffusion.github.io/">[link]</a></span> &#32;

<!-- SC_OFF --><div class="md"><p>Spent the last week coding diffusion Gemma from scratch. Was super fun. Thought I'd share it here &lt;3</p> <p>If you are looking for just the