FLock.io seeks to decentralise training and value alignment. We ensure that AI objectives match the public’s ethics and societal aims, that decision-making falls to communities, and that usefulness is a top priority.
FLock knocks down barriers impeding participation in the ecosystem. We allow developers to provide models, data, or compute in a modular way. The result: a plethora of fit-for-purpose models created by, for, and under the stewardship of the communities.
Yuma Pulse™
Data Ownership
Local training and hosting while data stay local. For crowdsourced data, contributors are fairly rewarded
Finetuning Foundation Models
Finetune LLMs, Stable Diffusion and more on your own or with other FLock nodes to lower data requirements
Scalable Infrastructure
Fast and compute-saving finetuning enabled by LoRA
Community-Owned
Finetuning and RAG co-ordinated on-chain, contributors of data, feedback, compute share rewards