Welcome to Psyche

Psyche is a system that enables distributed training of transformer-based AI models over the internet, aiming to foster collaboration between untrusted parties to create state-of-the-art machine learning models. It leverages a peer-to-peer distributed network for communication and data sharing.

This documentation provides a comprehensive guide to understanding, using, and developing with Psyche, whether you're an end-user looking to participate in a training run, a developer interested in contributing to the project, or just curious about how it all works.

Introduction

How does it work?

At its core, Psyche is a protocol that coordinates multiple independent clients to train a single machine learning model together. Rather than running on a centralized server farm with high-speed interconnects between every accelerator (GPUs, usually), Psyche distributes the training workload across many independent computers, each contributing a small piece to the overall training process.

Psyche is built to maintain training integrity without requiring participants to trust each other. Through a combination of consensus mechanisms, game theory, and careful protocol design, Psyche will ensure that the trained model remains coherent and consistent despite being trained across disparate machines.

Client Quickstart

If you are a client wanting to join an exiting training round you can refer to the join a run documentation