Distributed computing network Gensyn server deployment tutorial for beginners

Gensyn is a distributed computing network for training AI models. The network uses blockchain to verify whether deep learning tasks have been correctly executed and triggers payments through commands. RL Swarm is an open-source system for peer-to-peer reinforcement learning over the internet. Running a swarm node allows you to train your personal models for swarm intelligence. Each swarm executes RL inference as a group and uses a gossiping system (Hivemind) for collaborative model improvement. You can also connect your node to the Gensyn testnet to receive an on-chain identity that tracks your progress over time. RL Swarm is completely open and permissionless, which means you can run it on a basic consumer laptop at home or on powerful GPUs in the cloud. You can also try different models to see which performs best. Running Guide Note: Don't bother with CPU, it won't work. You need GPU. In DC, GPU scores come out quickly, but my CPU has been idle for a day. Requirements: - arm64 or x86 CPU, minimum 16GB RAM Or CUDA Devices (officially supported): - RTX 3090 - RTX 4090 - A100 series - H100 series Also requires: - Python >=3.10 (for Mac, you will likely need to upgrade) Recommended to rent GPU servers using VAST, the preferred GPU computing platform. [The rest of the tutorial continues with detailed technical instructions for setting up and running the RL Swarm system]