Sound event detection involves analyzing ongoing acoustic signals to identify and symbolize the various sounds within an auditory environment. This technology has multiple applications, such as enabling context-specific search and retrieval in multimedia databases, discreet monitoring in healthcare settings, and use in surveillance systems. This collection of papers provides insights into the field of sound event detection and the broader area of Sound AI. Real Time Sound Event Detection Awesome Sound Event Detection Sound Event Detection Transformer Sound Event Detection

Tyler Hobbs’ essay on “Flow Fields” delves into the use of flow fields in generative art, a technique he frequently employs. He explains the basics, including creating a grid of angles on a canvas and drawing curves through this field. Different methods for starting points and vector distortions, such as Perlin Noise, are explored. Hobbs also discusses combining flow fields with other techniques and experimenting beyond standard approaches. The essay is both a technical guide and an encouragement for artistic creativity in algorithmic artwork....

My own project https://github.com/marcinklimek/pchords

Has anyone made a read-only FUSE filesystem for a git repository where every commit is a folder and the folder contains all the files in that commit? The idea is that you could just run cd COMMIT_ID and poke around instead of checking out the commit and maybe the branches could be symbolic links to the commit folders? Git Mounter

Another explainer on a fun, esoteric topic: optimizing code with SIMD (single instruction multiple data, also sometimes called vectorization). Designing a good, fast, portable SIMD algorithm is not a simple matter and requires thinking a little bit like a circuit designer. Designing a SIMD Algorithm from Scratch