# Introduction **Overview** In web3, digital land serves as the basis for building the metaverse. It's a virtual space where individuals can own and construct their own digital assets, ranging from brands and businesses to entire virtual worlds. Owning a piece of digital land gives you the freedom to create and construct anything you desire. This groundbreaking idea is transforming how we view property ownership and the digital landscape. The opportunities are infinite, and there is no limit to the potential for innovation. So, if you're prepared to delve into the world of digital land ownership, fasten your seatbelt for an exhilarating journey. **Evergreen Lahser 7/8 Mission** The mission of Evergreen Lahser 7/8 in Detroit, MI is to empower the next generation of entrepreneurs by providing a city hub for networking, skill-building, entrepreneurship training, live events, branding, marketing, advertising, and innovation through our Metaverse in Upland platform. We are committed to infusing our real-life brand into the evergreen community by offering education on layer 2 environments, trainings, NFT give aways, and spark trains, as well as community contests, with a focus on Hip Hop culture. Our goal is to connect and empower individuals and businesses in the Detroit area, to unleash their full potential and drive economic growth in this dynamic industry. We strive to create a community where everyone can be a part of shaping the future of Detroit's hip-hop culture. We are dedicated to fostering a thriving entrepreneurship community that will be the cornerstone of our brand in the Metaverse. --- # 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://evergreen-lahser-7-8.gitbook.io/hgf-collective/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.