# Home

## Cortensor: Collaborative AI Frontier

Welcome to the official documentation for Cortensor, the pioneering decentralized AI inference and development platform. Here, you will find comprehensive resources to help you understand, set up, and maximize the potential of Cortensor.

### Overview

Cortensor aims to democratize AI by leveraging the power of decentralized networks and open-source models. By eliminating the constraints of centralized services, Cortensor provides a scalable, cost-effective solution for AI inference and development.

### Key Features

* **Decentralized AI Inference**: Harness the collective power of distributed computing for efficient and scalable AI processing.
* **Open-Source Models**: Utilize a variety of models for flexible and unrestricted AI applications.
* **Blockchain Integration**: Ensure secure, transparent transactions and incentivized collaborations.
* **Scalability and Efficiency**: Optimize resource usage and reduce operational costs.

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**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.\
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\&#xNAN;*<mark style="color:$warning;">**Important Notice**</mark>*

*<mark style="color:$warning;">Please be aware that the content may contain redundant and duplicate information, and many details are subject to change. Your understanding and patience are appreciated as we continue to improve and update this documentation.</mark>*


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# 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/home.md?ask=<question>
```

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.