Sparse Notes

Ilya Sutskever opens this Simons Institute lecture by admitting he almost gave the standard talk and decided against it. Instead he presents a set of results from years earlier at OpenAI, never published, on a question that had bothered him: supervised learning comes with a mathematical guarantee, and unsupervised learning does not. His claim is that it can, if you frame unsupervised learning as compression. This is the “Classic of the Week” pick, and it earns the label for a specific reason....

Two papers landed on arXiv the same day, from Cornell and TU Darmstadt, with the same idea: skip the general-purpose query engine and have an LLM agent compile each SQL query directly into specialized C++. GenDB and BespokeOLAP report 10x over DuckDB on TPC-H, 460x over Postgres, and per-query wins up to 1,466x. Alex Kouzemtchenko, CTO of Espresso AI, walked Papers We Love Brooklyn through both — and the interesting part of the talk is the half spent on what the numbers don’t say....

Weekly Paper Notes — one of the top picks from the 2026-08-29 CS paper digest. Area: AI / Machine Learning. Authors: Lukas Kuhn, Lucas Maes, Giuseppe Serra, Quentin Le Lidec, Yann LeCun, Randall Balestriero, Florian Buettner (German Cancer Research Center / DKTK / Goethe University Frankfurt, Mila, Université de Montréal, Brown University, Courant Institute NYU, AMI Labs) arXiv: 2608.27395 · PDF · Project page TL;DR Self-supervised video encoders have been expensive twice over: video carries an order of magnitude more tokens than an image, and the dominant methods add machinery on top of that cost purely to keep representations from collapsing....

Weekly Paper Notes — one of the top picks from the 2026-08-29 CS paper digest. Area: Operating Systems / Systems. Authors: Rui Ueyama (The University of Tokyo) arXiv: 2608.23228 · PDF · Code TL;DR mold is a Unix/Linux ELF linker built around one commitment: every major pass is a data-parallel loop over a homogeneous array, and nothing important is left sequential. The enabling move is decoupling input parsing from symbol resolution....

Weekly Paper Notes — the Seminal Paper of the Week for the 2026-08-29 digest. Area: Operating Systems. Authors: Dennis M. Ritchie and Ken Thompson (Bell Laboratories) Published: Communications of the ACM, Vol. 17, No. 7, July 1974, pp. 365–375. DOI: 10.1145/361011.361061 Why the paper still matters Most influential systems papers describe something large. This one describes something conspicuously small, and the smallness is the argument. The system it presents ran on a PDP-11/45 with 144K bytes of core, of which the resident kernel occupied roughly 42K — about 16K words of code and data....

Anima Anandkumar spent 83 minutes on Latent Space explaining a specific architectural claim: transformers are the wrong tool for physical simulation, and the reason is not compute budget but a mismatch in what the architecture assumes about its inputs. She has the receipts — her group’s weather model, FourCastNet, is deployed at a national weather agency and runs tens of thousands of times faster than the numerical models it replaces....

Most conversations about making agents better are really conversations about making models better. Alex Krentsel — a Berkeley systems PhD student working with Martin Casado and Ankur Goyal — spends this Latent Space episode arguing the opposite: the model is fine, and the leverage now lives in the harness, the “body we provide to the brain.” Exo, the project he introduces, is an agent that can safely edit every aspect of itself at runtime....

Weekly Paper Notes — one of the top picks from the 2026-08-22 CS paper digest. Area: Operating Systems / Serving Systems. Authors: Chaokun Chang, Yukun Zhou, Kaihua Fu, Dakai An, Tianyu Feng, Hanfeng Lu, Sheng Yao, Pu Guo (HKUST), Yinghao Yu (Alibaba Group), Yizhou Shan (ByteDance), Bo Li, Binhang Yuan, Wei Wang (HKUST) arXiv: 2608.15127 · PDF TL;DR Every serving system in production today — vLLM, SGLang, TensorRT-LLM — was designed around a single assumption: the unit of work is a token-generation request, and the GPU is where the time goes....

Andy Pavlo opens CMU’s database systems course with a claim that reframes most of what practitioners argue about online: the problems are not new. The hardware changed; the problems didn’t. This week’s Classic of the Week is his Lecture 1 — course information plus a compressed history of database systems from the 1960s to the present. It’s the single best hour for understanding why databases look the way they do, and it comes with an implicit warning: if you don’t know this history, you will spend your career re-litigating settled debates....

When Anthropic announced it would watermark text output from Claude models, Sebastian Raschka posted a short explanation of the mechanism. The post went unexpectedly viral — not because watermarking is exciting, but because almost nobody could say concretely what it does. He planned a ten-slide follow-up. It became fifty. The result is one of the better explainers of the year, and it doubles as a clean walkthrough of how LLM sampling actually works....