3 Explorations in Gen~

Following the release of Gregory Taylor and Graham Wakefield's new book of Gen inspiration, we invited 3 artists to each produce a patch for us that does something with gen~. Each of these artists have demonstrated a serious mastery of Gen patching in their frequent posts online, and we were excited to see what they came up with.
The patches they sent us are all impressive demonstrations of what is possible with Gen, and exceeded all of my expectations. Whether you're looking for some good Gen tricks, or just want to experience the patches, there's a lot here to enjoy. From Daniele's rhythmic granular synthesis patch, to Fendoap's fully realized generative music, and Massimiliano's math-intensive and thoroughly documented algorithmic modelling, you'll find 3 very different approaches to patching. I hope you download the patches below and tune into their social media feeds to see more of their incredible Max patches.

Daniele Fabris (@daniele.fabris)

This is a patch for sample playback implementing a simple algorithm of granular
synthesis in gen~. It creates a constant auto-re-triggered stream of crossfading sections
of the source sample.
The pitch, read position and windowing of each grain can be modulated to reach
deconstructed sounds in organic rhythmic patterns.

Find more of Daniele's work on Instagram

Fendoap (y.o.fendoap)

Here's a patch that creates music with just one gen~ object.
Global transport, metro, kick, hi-hat, synth, delay, reverb,sequencer, etc. have been written in a single gen~ object.
It's all written in gen~, so you can write it into daisy with using oopsy.
If you write various things using gen~, your understanding will deepen. gen~ is good for learning dsp.

Find more of Fendoap's work on Instagram

Massimiliano Cerioni (@cerionimusic)

I have implemented a two species competition-cooperation model in Gen using Lotka-
Volterra equations, to generate a controlled chaos with very specific behaviors like asymptotic convergence, periodicity/quasi-periodicity, attractor-like motion, distributed pseudo-randomness, etc. I was inspired by the work and the researches of Iannis Xenakis and Rob Hordijk.

Find more of Massimiliano's work on Instagram.