Decentralized AI: Super Swarm of Models. Fine-tuning is the core of our Decentralized AI Super Swarm! We're building a decentralized AI ecosystem where a super swarm of specialized, smaller models collaborates to perform complex tasks, coordinated through a community-driven, modular architecture and governed by DAOs that manage LLM weights. This approach sidesteps the resource-intensive, monolithic LLMs of centralized giants, offering asymmetric advantages in efficiency, innovation, and community engagement. A "super swarm" refers to a decentralized network of AI models, each specialized for specific tasks or domains, that collaborate to perform complex, multi-step tasks. Unlike a single, general-purpose LLM (e.g., GPT-4), which handles diverse tasks within one model, a super swarm distributes intelligence across many smaller models, coordinated through a decentralized protocol. This mimics biological swarms (e.g., ant colonies), where simple agents collectively achieve sophisticated outcomes. Users & creators fine-tune models or contribute datasets, earning rewards for their work — think data curation, model training, or testing.