> For the complete documentation index, see [llms.txt](https://artificialsupercomp.gitbook.io/artificial-super-computer/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://artificialsupercomp.gitbook.io/artificial-super-computer/asc-ecosystem.md). # ASC Ecosystem The Artificial Super Computer network operates through the synergy of five key participants: miners, developers, users, token holders, and the Artificial Super Computer DAO. Miners within our network are differentiated into three distinct types: Containers, Checkers, and Indexers. This structured categorization ensures efficient consensus and optimal service rendering across the network. At the heart of our ecosystem lies the CORE token, which is pivotal in driving user engagement and fostering the development of a wide array of applications. It also plays a critical role in broadening our user community. This ecosystem is designed to fuel a continuous cycle of growth and innovation, making the Artificial Super Computer network a self-perpetuating engine for development and expansion. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## 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, and the optional `goal` query parameter: ``` GET https://artificialsupercomp.gitbook.io/artificial-super-computer/asc-ecosystem.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. 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.