Tootfinder

What I've planned to be doing: adding CPU_FLAGS_* support to #NumPy package in #Gentoo.
What I am doing instead: digging through #ARM documentation, kernel sources, NumPy sources to figure out what's missing from CPU_FLAGS_ARM and how to detect it.

Czym miałem się zajmować: dodawaniem wsparcia CPU_FLAGS_* do paczek #NumPy w #Gentoo.
Czym się zajmuję: przegrzebywaniem dokumentacji #ARM, źródeł jądra, źródeł NumPy, by ogarnąć brakujące flagi w CPU_FLAGS_ARM i sposó…

Very interesting origin story of Scipy/Numpy which is the foundation of so much #ML stuff and why Python became the dominant language for ML / #AI.
https://www.youtube.com/watch?v=-xhai2iu_QY

"Vibe coding" is one of the dumbest ideas that I've heard in a long time.
Yes, there are often reasons to use tools (such as Knuth's books) to lookup methods. And well established and tested libraries are great. (Thank you "numpy".)
But "vibe coding" just turns programmers into little more than proofreaders - proofreading complex and often boring material. That is putting the cart before the horse. (Is there a modern phrase for that adage?…

An AI-powered coding tool wiped out a software company’s database, then apologized for a ‘catastrophic failure on my part’
An experiment with an AI coding tool took a disastrous turn when an AI agent reportedly deleted a live company database during an active code freeze.

The Syntax and Semantics of einsum
Maurice Wenig, Paul G. Rump, Mark Blacher, Joachim Giesen
https://arxiv.org/abs/2509.20020 https://arxiv.org/pdf/2509.20…

The Syntax and Semantics of einsum
In 2011, einsum was introduced to NumPy as a practical and convenient notation for tensor expressions in machine learning, quantum circuit simulation, and other fields. It has since been implemented in additional Python frameworks such as PyTorch and TensorFlow, as well as in other programming languages such as Julia. Despite its practical success, the einsum notation still lacks a solid theoretical basis, and is not unified across the different frameworks, limiting opportunities for formal rea…

QUBOLite: A lightweigth Python toolkit for QUBO
Sascha M\"ucke, Thore Gerlach, Nico Piatkowski, Lukas Thei{\ss}inger
https://arxiv.org/abs/2509.21321 https://

QUBOLite: A lightweigth Python toolkit for QUBO
We present QUBOLite, a Python package for the creation, manipulation, analysis, and solution of Quadratic Unconstrained Binary Optimization (QUBO) instances. Built as a thin wrapper around NumPy arrays, QUBOLite combines efficient numerical operations with high-level abstractions for tasks ranging from instance generation to preprocessing, analysis, and solving strategies, both exact and approximate. The package includes implementations of the QPRO+ algorithm by Glover et al. for identifying st…

kh2d-solver: A Python Library for Idealized Two-Dimensional Incompressible Kelvin-Helmholtz Instability
Sandy H. S. Herho, Nurjanna J. Trilaksono, Faiz R. Fajary, Gandhi Napitupulu, Iwan P. Anwar, Faruq Khadami, Dasapta E. Irawan
https://arxiv.org/abs/2509.16080

kh2d-solver: A Python Library for Idealized Two-Dimensional Incompressible Kelvin-Helmholtz Instability
We present an open-source Python library for simulating two-dimensional incompressible Kelvin-Helmholtz instabilities in stratified shear flows. The solver employs a fractional-step projection method with spectral Poisson solution via Fast Sine Transform, achieving second-order spatial accuracy. Implementation leverages NumPy, SciPy, and Numba JIT compilation for efficient computation. Four canonical test cases explore Reynolds numbers 1000--5000 and Richardson numbers 0.1--0.3: classical shear…