Sparse Notes
Technical notes on DevOps, Kubernetes, Software Engineering, and AI.
Classic of the Week: It's Time for Operating Systems to Rediscover Hardware (Timothy Roscoe)
Timothy Roscoe (ETH Zurich, co-lead of the Barrelfish multikernel and the Enzian research computer) gave the joint OSDI/ATC keynote in 2021 and announced up front that he’d chosen the “keynote as therapy” format. What he unloads is a simple argument that keeps getting more true: the machine Linux thinks it runs on doesn’t exist, the thing actually managing a modern computer was never designed by anyone, and the systems research community has mostly stopped looking....
Congestion Avoidance and Control (Jacobson, 1988)
Weekly Paper Notes — the Seminal Paper of the Week for the 2026-10-03 digest. Area: Networking / Systems. Authors: Van Jacobson (Lawrence Berkeley Laboratory), with Michael J. Karels (UC Berkeley) on the revised version Published: Proceedings of ACM SIGCOMM ‘88, Stanford, August 1988; Computer Communication Review 18(4), pp. 314–329. DOI: 10.1145/52324.52356 Why the paper still matters In October 1986 the link between Lawrence Berkeley Laboratory and UC Berkeley, about 400 yards apart and three gateway hops, went from 32 kbit/s to 40 bit/s....
Context Language Models
Weekly Paper Notes — one of the top picks from the 2026-10-03 CS paper digest. Area: NLP. Authors: Rulin Shao, Shannon Zejiang Shen, Junjie Oscar Yin, Yuetai Li, Minheng Wang, Hamish Ivison, Radha Poovendran, Nathan Lambert, Teng Xiao, Mike Lewis, Wen-tau Yih, Luke Zettlemoyer, Pang Wei Koh (University of Washington, Meta Superintelligence Labs, MIT, Trillium Labs) arXiv: 2609.37725 · PDF · Code TL;DR A standard language model’s context only grows: each turn appends the model’s output, c_{t+1} = c_t ⊕ f(c_t)....
Mixture-of-Kittens: MoE Megakernel for NVL72s
Weekly Paper Notes — one of the top picks from the 2026-10-03 CS paper digest. Area: Distributed Computing. Authors: Stuart H. Sul, Nash Brown (Stanford, Cursor Research), Henry Wildermuth, William Lin, Federico Cassano (Cursor Research), Christopher Ré (Stanford) arXiv: 2609.36070 · PDF · Code TL;DR Mixture-of-Kittens (MoK) is the MoE training kernel Cursor uses to train Composer on GB300 NVL72 racks. The paper’s opening finding is uncomfortable for anyone who has invested in MoE communication libraries: on a 72-GPU NVLink domain, existing expert-parallel systems built for InfiniBand often lose to a naive PyTorch + NCCL baseline, and in nearly half of the evaluated configurations the naive baseline beats every alternative....
Security in the LLM Age (Greg Kroah-Hartman, Kernel Recipes 2026)
A year ago Greg Kroah-Hartman told a security conference the Linux kernel was issuing 50 CVEs a week and everyone thought that was insane. The kernel is now issuing 33 a day. His Kernel Recipes 2026 talk is aimed at kernel developers and maintainers, not the general public, and its refrain is “do not panic.” What makes it worth an hour is that he backs the refrain with raw data: he got the full report behind this year’s most publicised AI bug hunt and went through it line by line....
The Death of the Code Review: What the Data Actually Says (Laurie Voss)
Developers who switched on autonomous coding agents wrote 741% more code and shipped 30% more software. Laurie Voss (npm co-founder, now head of developer relations at Arize AI) opens with that pair of numbers from a study of more than 100,000 GitHub developers, and spends the next 24 minutes on one question: if review is the bottleneck, what are teams actually doing about it? The talk is a literature review delivered at speed....
An Observation on Generalization
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....
Can LLMs Build a 10x Faster Database?
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....
LeVJEPA: Efficient & Scalable Video Pretraining without the Heuristics
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....
mold: A Massively Parallel Linker
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....