> For the complete documentation index, see [llms.txt](https://docs.getcherry.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.getcherry.ai/welcome/why-bittensor.md). # Why Bittensor? ## Embracing Decentralization and Freedom The integration of Bittensor technology into Cherry, facilitated through our partnership with VectorChat, is a cornerstone of our commitment to providing an unparalleled AI companionship experience. Bittensor’s unique attributes align seamlessly with the core principles of Cherry, especially in terms of freedom of expression and decentralized operation.\ \ Bittensor's decentralized and permissionless nature is fundamental to its appeal and utility within the Cherry platform. This approach ensures maximum freedom, both in terms of what you can create with your Cherries and how they can express themselves. ## The Role of Bittensor in Cherry's Philosophy * **Permissionless and Decentralized LLMs**: Bittensor’s technology is at the forefront of permissionless, decentralized Large Language Models (LLMs), both in terms of the models themselves and the computing power required to run them. This aspect is crucial for Cherry, as it provides the freedom and flexibility needed to fully realize our vision. * **Freedom of Expression**: At the heart of Cherry's philosophy is the belief in unbridled freedom of expression. Bittensor's infrastructure empowers this vision, allowing for the creation and interaction with AI companions in ways that are unrestricted by traditional centralized models. * **Unleashing Creativity**: With Bittensor, we can offer our users the liberty to explore, create, and interact with their Cherries in any manner they see fit. This freedom is essential for fostering genuine, dynamic, and deeply personal relationships between users and their AI companions. --- # 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://docs.getcherry.ai/welcome/why-bittensor.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.