# What is Cortensor? Cortensor is a cutting-edge decentralized AI inference and development platform. It is designed to democratize access to artificial intelligence by leveraging the power of decentralized networks and open-source models. By moving away from centralized AI services, Cortensor aims to provide a scalable, cost-effective, and efficient solution for AI inference and development. ## **Key Characteristics** * Decentralized AI Inference: Cortensor utilizes a network of distributed computing resources to perform AI tasks, enhancing efficiency and scalability while reducing reliance on large, centralized data centers. * Open-Source Models: The platform supports a variety of open-source AI models, allowing for flexible and unrestricted AI applications. Users can fine-tune and deploy these models to suit their specific needs. * Blockchain Integration: Cortensor integrates blockchain technology to ensure secure, transparent transactions and incentivized collaborations within the network. This promotes trust and innovation across the community. * Community-Driven Development: Cortensor encourages contributions from its community, fostering an ecosystem where innovation is rewarded, and diverse AI solutions can thrive. ## **Objectives** * Democratize AI: Making AI technology accessible to a broader audience by reducing barriers to entry. * Promote Innovation: Encouraging the development of new AI models and applications through a fair and incentivized marketplace. * Enhance Efficiency: Optimizing resource usage and reducing operational costs associated with AI development and inference. *** **Disclaimer:** This page and the associated documents are currently a work in progress. The information provided may not be up to date and is subject to change at any time. --- # 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.cortensor.network/introduction/what-is-cortensor.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.