For context, I have no CS background (terminals scare me), studied evolutionary biology in undergrad, did behavior analysis work for children with autism, and spent the last few years working full time as an independent artist.

While building agent infrastructure to help with the business demands of artistry, I developed a hypothesis about current LLM architecture that I want to test.

The core idea is nature has never produced higher orders of intelligence through single isolated units. Yet every frontier LLM is based on single model architecture. I want to change that. I'm placing several open source models into a living training environment with birth/death conditions, extinction events, commerce, and even marriages between models. The goal is to recreate natural selection within a training environment to force model specialization and evolution. I also have some preliminary ideas on minimizing the attention bottleneck in current LLMs by introducing "emotions" as a model parameter.

Happy to get into the more technical details in the comments. Will be periodically posting my research updates here. If you want to support the experiment: https://www.gofundme.com/f/stop-wasting-water-on-data-centers-a-safe-roadmap-for-ai