**fed_AI is live.** fed_AI is an experiment in decentralised AI infrastructure. The goal is simple: break large AI systems into composable, auditable services that can be run by independent operators, routed dynamically, and paid for on a pay-as-you-go basis. Instead of one opaque model doing everything, fed_AI treats AI as a network: * Routers decide where work goes * Nodes specialise in narrow tasks * Models are pluggable, replaceable, and swappable * Capacity comes from many machines, not one provider This is not about chasing scale for its own sake. It is about resilience, cost control, locality, and choice. Key principles: * Open source by default * No data scraping or silent retention * Deterministic routing and traceable execution * Friendly to small operators and hobbyist hardware * Works alongside existing proprietary and open models Early focus is on proof-of-concept code, clear documentation, and a threat model that assumes untrusted participants. This is experimental. Expect rough edges. Expect iteration. If you are interested in decentralised systems, AI infra, or running useful services on ordinary machines, this project is for you. More soon. #fedAI #Nostr #DecentralisedAI #OpenSource #DistributedSystems