#linuxaudio has reach more stability than ever, opensource made possible an incredible tool as #NAM and great developers continue to write code to made usefull essential tool as #stompbox. I belive in this project that aim to democratize #guitar gear by using a simple #raspberry.

marcomazzocco.com/i-ditched-a-…

I Ditched a $3,000 Pedalboard for a $90 Raspberry Pi and I'm Not Sorry | Marco Mazzocco

Raspberry as a full rig for live performance

^{Marco Mazzocco}

So okay I've been trying to check out whether using my Linux PC as a guitar amp would be viable and I keep running into this NAM thing (neuralampmodeler.com/)

And very little else? And I'm like... come on. The only amp sim available, or at least one so popular it drowns out all other options, and it's based on a neural network? That sounds like "AI" hype driven overkill, right? At least to me as a complete newcomer.

Is there really nothing decent that just takes the obvious approach of applying simple, mathematically understandable algorithms to produce effects? Does it make sense somehow to use a neural network to do this? Is it performant? What's going on?

#guitar #ElectricGuitar #LinuxMusic #LinuxAudio #NAM #NeuralAmpModeler

Neural Amp Modeler | Highly-accurate free and open-source amp modeling plugin

Neural Amp Modeler is a free and open-source technology for modeling guitar amplifiers and pedals using deep learning. Get started making music with NAM, contribute to the code, or build your own products using state of the art modeling.

^{Neural Amp Modeler}