# 1. Introduction ***1.1 Background*** \ In today’s age of information explosion, the internet generates vast amounts of data every second. This data is not only a societal asset, encompassing knowledge, information, and various creative contents, but it also holds enormous commercial value. However, the sheer volume of data brings about a significant challenge in efficient retrieval and selection. A large amount of useless or irrelevant data not only impacts the direction of artificial intelligence (AI) training but also leads to the waste of computational resources. With the rapid development of AI technology, its applications are becoming increasingly widespread across various industries, from healthcare and finance to entertainment. However, the performance of AI models largely depends on high-quality and diverse datasets. Traditional data collection and processing methods can no longer meet the high demands of modern AI for data, creating substantial opportunities for the GAEA project to grow. ***1.2 Mission and Vision*** \ GAEA's mission is to make data more valuable. By constructing a decentralized value data layer, GAEA aims to optimize data selection, providing more efficient and valuable datasets for AI training, thus promoting the development of AI technology. Our vision is to create a silicon-based universe where every user participates, making everyone a creator and "god" of this new world. ***1.3 Overview*** \ GAEA is a DePIN (Decentralized Physical Infrastructure Networks) network built on blockchain technology and decentralized networks, open, transparent, and community-driven. Users can share their idle network resources to help collect and optimize data for AI training, while earning rewards through the GAEA point system. The core of GAEA lies in constructing a value data layer that enhances the value of data in AI training through efficient data processing and incentive mechanisms, realizing the vision of "everyone is a creator." --- # 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://doc.aigaea.org/1.-introduction.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.