Beyond Market Intelligence/Winograd Convolution

Winograd Convolution

Winograd Convolution on Beyond Market Intelligence: a running collection of one story we have gathered and hand-picked because they are worth your time. Every post here touches on winograd convolution in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around winograd convolution, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.

I implemented the YOLO26n model inference from scratch using ARM64 Assembly Language (No framework) [P]
Machine Learning

I implemented the YOLO26n model inference from scratch using ARM64 Assembly Language (No framework) [P]

This impressive Bachelor's Final Project delivers a complete, from-scratch YOLO26n inference engine built using ARM64 Assembly Language and C—no frameworks required. The implementation prioritizes edge AI execution on Raspberry Pi 4, incorporating critical optimizations like ARM NEON SIMD, Winograd convolution, and cache-aware tiling. While performance gains didn't fully meet initial expectations, this project offers valuable insights into low-level neural network acceleration. For further exploration of efficient data encoding, consider “Ink & Switch Introduces Bijou64.” Repository: https://github.com/mohammad-ghaderi/YOLO26