Tootfinder

Apple seems to be working on adding CUDA support to open-source ML framework MLX, which may mean that code developed using MLX would work with CUDA (Malcolm Owen/AppleInsider)
https://appleinsider.com/articles/25/0

Apple Silicon machine learning code may become more easily portable to Nvidia hardware
A project is trying to cut the cost of making machine learning applications for Nvidia hardware, by developing on an Apple Silicon Mac and exporting it to CUDA.

From Chaos to Automation: Enabling the Use of Unstructured Data for Robotic Process Automation
Kelly Kurowski, Xixi Lu, Hajo A. Reijers
https://arxiv.org/abs/2507.11364

From Chaos to Automation: Enabling the Use of Unstructured Data for Robotic Process Automation
The growing volume of unstructured data within organizations poses significant challenges for data analysis and process automation. Unstructured data, which lacks a predefined format, encompasses various forms such as emails, reports, and scans. It is estimated to constitute approximately 80% of enterprise data. Despite the valuable insights it can offer, extracting meaningful information from unstructured data is more complex compared to structured data. Robotic Process Automation (RPA) has ga…

Precision Spatio-Temporal Feature Fusion for Robust Remote Sensing Change Detection
Buddhi Wijenayake, Athulya Ratnayake, Praveen Sumanasekara, Nichula Wasalathilaka, Mathivathanan Piratheepan, Roshan Godaliyadda, Mervyn Ekanayake, Vijitha Herath
https://arxiv.org/abs/2507.11523

Precision Spatio-Temporal Feature Fusion for Robust Remote Sensing Change Detection
Remote sensing change detection is vital for monitoring environmental and urban transformations but faces challenges like manual feature extraction and sensitivity to noise. Traditional methods and early deep learning models, such as convolutional neural networks (CNNs), struggle to capture long-range dependencies and global context essential for accurate change detection in complex scenes. While Transformer-based models mitigate these issues, their computational complexity limits their applica…

👀 This 1D camera captures 2D images of things it can’t see
#camera

This 1D camera captures 2D images of things it can’t see | Arduino Blog
Yes, the title of this article sounds pretty crazy. But not only is it entirely possible through the lens of physics, but it is also practical to achieve in the real world using affordable parts. Jon Bumstead pulled it off with an Arduino, a photoresistor, and an inexpensive portable projector. Today’s digital camera sensors are […]

Magnetic reconnection sustains the mass budget of the solar wind
Yajie Chen, Hardi Peter, Damien Przybylski, Haruhisa Iijima, Lakshmi Pradeep Chitta
https://arxiv.org/abs/2509.11692

Magnetic reconnection sustains the mass budget of the solar wind
The solar wind originates from regions of open magnetic fields on the Sun, but the relevant processes remain unsolved. We present a self-consistent numerical model of the source region of the wind, in which jets similar to those observed on the Sun naturally emerge due to magnetic reconnection between closed and open magnetic fields. In this process material is transferred from closed to open field lines and fed into the solar wind.We quantify the mass flux through the magnetic field connected …

Sentiment Feedback in Equity Markets: Asymmetries, Retail Heterogeneity, and Structural Calibration
Lucas Marques Sneller
https://arxiv.org/abs/2509.11970 https://

Sentiment Feedback in Equity Markets: Asymmetries, Retail Heterogeneity, and Structural Calibration
We study how sentiment shocks propagate through equity returns and investor clientele using four independent proxies with sign-aligned kappa-rho parameters. A structural calibration links a one standard deviation innovation in sentiment to a pricing impact of 1.06 basis points with persistence parameter rho = 0.940, yielding a half-life of 11.2 months. The impulse response peaks around the 12-month horizon, indicating slow-moving amplification. Cross-sectionally, a simple D10-D1 portfolio earns…

Very-low-field MRI scanners: from the ideal to the real permanent magnet array
Umberto Zanovello, Alessandro Arduino, Vittorio Basso, Luca Zilberti, Alessandro Sola, Andrea Agosto, Luca Toso, Oriano Bottauscio
https://arxiv.org/abs/2509.11762

Very-low-field MRI scanners: from the ideal to the real permanent magnet array
Very-low-field MRIs are becoming increasingly popular due to their portability and adaptability to different environments. They are being successfully used for various clinical applications, leading to a paradigm shift in the way imaging care is typically performed. The development of low-cost MRI scanner prototypes began a few years ago, with some interesting and promising open-source projects emerging in both hardware and software design. Using permanent magnets (PMs) to generate the static m…

Taste is used here as a research instrument, not a metaphor.
Each work translates a regional ecological transformation into a reproducible, time-based edible score
paired with a data-driven abstract drawing that represents perceived taste.
Together, an instructional certificate (containing the edible score),
a data-driven abstract drawing,
and a Bioregional Context Dossier form a single artwork
that can be performed, conserved, and collected.

Taste Cartographies Documenting Anthropocene Terroir Through Systematic Flavor Analysis — Beth Ames Altringer Eagle Portfolio
Taste Cartographies Documenting Anthropocene Terroir Through Systematic Flavor Analysis Project focus: Systematic translation of regional ecological systems...

Crosslisted article(s) found for cs.PF. https://arxiv.org/list/cs.PF/new
[1/1]:
- Mixed-Precision Performance Portability of FFT-Based GPU-Accelerated Algorithms for Block-Triangu...
Sreeram Venkat, Kasia Swirydowicz, Noah Wolfe, Omar Ghattas

Performant Unified GPU Kernels for Portable Singular Value Computation Across Hardware and Precision
Evelyne Ringoot, Rabab Alomairy, Valentin Churavy, Alan Edelman
https://arxiv.org/abs/2508.06339

Performant Unified GPU Kernels for Portable Singular Value Computation Across Hardware and Precision
This paper presents a portable, GPU-accelerated implementation of a QR-based singular value computation algorithm in Julia. The singular value ecomposition (SVD) is a fundamental numerical tool in scientific computing and machine learning, providing optimal low-rank matrix approximations. Its importance has increased even more in large-scale machine learning pipelines, including large language models (LLMs), where it enables low-rank adaptation (LoRA). The implemented algorithm is based on the …