# Introduction to FLock.io FLock.io seeks to decentralise training and [value alignment](https://en.wikipedia.org/wiki/Reinforcement_learning_from_human_feedback). 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. Our incentivised platform democratises AI agent training, fine-tuning and inferencing. It halts user data collection, and enables equitable distribution of rewards and widespread governance. Leveraging blockchain technology and AI, FLock provides a powerful environment for dealing with large datasets. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.flock.io/what-is-flock/introduction-to-flock.io.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.