Tootfinder

Google warns that the EU risks undermining its own competitiveness drive with the "tech sovereignty package" the bloc is set to present in the spring (Barbara Moens/Financial Times)
https://www.ft.com/content/0847914c-be27-4573-8600-8cdb54e604b7

from my link log —
Keeping secrets: Diffie-Hellman and the NSA.
https://stanfordmag.org/contents/keeping-secrets
saved 2020-10-17 https://

Keeping Secrets
Four decades ago, university researchers figured out the key to computer privacy, sparking a battle with the National Security Agency that continues today.

Series B, Episode 10 - Voice from the Past
GLYND: The evidence, my friends. [Holds tapes] Surveillance report on Supreme Commander Servalan's attempt to cheat the Federation of one hundred million credits in return for the supercomputer Orac. Confidential report on your trial, Blake, and the subsequent elimination of your defence lawyer when he discovered that the evidence against you had been falsified. Need I continue? [Closes case of tapes] Enough, as I have said, to convict th…

Equilibria: Fair Multi-Tenant CXL Memory Tiering At Scale
Kaiyang Zhao, Neha Gholkar, Hasan Maruf, Abhishek Dhanotia, Johannes Weiner, Gregory Price, Ning Sun, Bhavya Dwivedi, Stuart Clark, Dimitrios Skarlatos
https://arxiv.org/abs/2602.08800 https://arxiv.org/pdf/2602.08800 https://arxiv.org/html/2602.08800
arXiv:2602.08800v1 Announce Type: new
Abstract: Memory dominates datacenter system cost and power. Memory expansion via Compute Express Link (CXL) is an effective way to provide additional memory at lower cost and power, but its effective use requires software-level tiering for hyperscaler workloads. Existing tiering solutions, including current Linux support, face fundamental limitations in production deployments. First, they lack multi-tenancy support, failing to handle stacked homogeneous or heterogeneous workloads. Second, limited control-plane flexibility leads to fairness violations and performance variability. Finally, insufficient observability prevents operators from diagnosing performance pathologies at scale.
We present Equilibria, an OS framework enabling fair, multi-tenant CXL tiering at datacenter scale. Equilibria provides per-container controls for memory fair-share allocation and fine-grained observability of tiered-memory usage and operations. It further enforces flexible, user-specified fairness policies through regulated promotion and demotion, and mitigates noisy-neighbor interference by suppressing thrashing.
Evaluated in a large hyperscaler fleet using production workloads and benchmarks, Equilibria helps workloads meet service level objectives (SLOs) while avoiding performance interference. It improves performance over the state-of-the-art Linux solution, TPP, by up to 52% for production workloads and 1.7x for benchmarks. All Equilibria patches have been released to the Linux community.
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Layer-Resolved Impurity States Reveal Competing Pairing Mechanisms in Trilayer Nickelate Superconductor La$_4$Ni$_3$O$_{10}$
Suyin Zheng, Tao Zhou
https://arxiv.org/abs/2512.07636

"For Levy and Newborn, the stakes were clear, and the title of the first chapter of the book says it all: “The Challenge is World Champion Kasparov”. Said chapter describes in detail the match between a first iteration of a chess supercomputer by IBM, the less well-known “Deep Thought”. It was a strong contender, having defeated quite a few grandmasters along the way (including the aforementioned Levy), but was no match for Kasparov in August 1989."

David Levy & Monty Newborn
The literature about and around chess is too long to enumerate in an article of a thousand words, and this is clearly not my intent. If you want to learn chess, there are so many good books around, it is hard to pick just one. There are, however, fewer books explaining the art of how to teach a computer to play chess; and the one chosen for this issue of the Library section does a magnificent job at precisely that.

LoD-Structured 3D Gaussian Splatting for Streaming Video Reconstruction
Xinhui Liu, Can Wang, Lei Liu, Zhenghao Chen, Wei Jiang, Wei Wang, Dong Xu
https://arxiv.org/abs/2601.18475 https://arxiv.org/pdf/2601.18475 https://arxiv.org/html/2601.18475
arXiv:2601.18475v1 Announce Type: new
Abstract: Free-Viewpoint Video (FVV) reconstruction enables photorealistic and interactive 3D scene visualization; however, real-time streaming is often bottlenecked by sparse-view inputs, prohibitive training costs, and bandwidth constraints. While recent 3D Gaussian Splatting (3DGS) has advanced FVV due to its superior rendering speed, Streaming Free-Viewpoint Video (SFVV) introduces additional demands for rapid optimization, high-fidelity reconstruction under sparse constraints, and minimal storage footprints. To bridge this gap, we propose StreamLoD-GS, an LoD-based Gaussian Splatting framework designed specifically for SFVV. Our approach integrates three core innovations: 1) an Anchor- and Octree-based LoD-structured 3DGS with a hierarchical Gaussian dropout technique to ensure efficient and stable optimization while maintaining high-quality rendering; 2) a GMM-based motion partitioning mechanism that separates dynamic and static content, refining dynamic regions while preserving background stability; and 3) a quantized residual refinement framework that significantly reduces storage requirements without compromising visual fidelity. Extensive experiments demonstrate that StreamLoD-GS achieves competitive or state-of-the-art performance in terms of quality, efficiency, and storage.
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