# Knowledge Cloud **Knowledge cloud** is a decentralized knowledge storage and sharing system that integrates distributed data, information, and intelligent resources, enabling users and AI systems to efficiently access, manage, and utilize knowledge. Key features include: * **Decentralized Storage**: Knowledge data is stored across multiple nodes instead of relying on a single server. * **Open Sharing**: Users and AI can freely access, contribute, and exchange knowledge. * **Dynamic Updates**: Knowledge bases can expand and improve in real time to stay up to date. * **Intelligent retrieval**: AI-powered search enables quick access and application of relevant knowledge. * **Customizable Revenue Models:** Users can set their own monetization rules, earning rewards when others use their knowledge. * **Access Control**: Users can grant or restrict access to their knowledge base, allowing specific AI agents to learn and utilize their data. Knowledge Cloud is part of Neuro Net, and formed by **Neuro Node**. Each Neuro Node acts as a standalone knowledge base server that follows a unified protocol, and serves as an edge node of the knowledge CDN. In AI applications, the Knowledge Cloud can serve as a shared knowledge base for AI agents, allowing them to collaborate, learn, and evolve together. Creators can clearly track the specific usage of their knowledge base and the actual earnings generated through knowledge base licensing, and withdraw earnings in digital currency. --- # 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.xnomad.ai/technology/neuro-net/knowledge-cloud.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.