# Introduction Today we are still physical human beings consuming digital content on the internet which is unrelated to our surroundings. We believe that the next generation of life is living with agents in a blended universe by physical and digital world. Zeno is a comprehensive platform designed to create a persistent, shared digital layer over the physical world. Our mission is to establish a set of models and a robust system to describe and connect the physical world with dynamic virtual worlds. By digitizing physical spaces and overlaying multiple parallel virtual worlds, we offer a blended universe for real world agents, including human beings, robots, smart devices, and virtual world agents, including human controlled avatars, AI-powered NPCs, and many other bot-like programs to live together. Like the physical world that is ruled by physics laws, the virtual worlds are driven by virtual world engines with alternative sets of rules, similar to reality or purely magical. Real world localization is the key here. We have a high precision fused visual positioning algorithm and vision world model for the platform to determine a pose (position and orientation) of an agent in the real world, with the agent's camera and other sensor signals. Through spatial anchors, these poses are linked to virtual worlds, allowing agents to understand its real world location and surrounding physical environment, discover and interact with virtual objects and other agents with applications on the Zeno platform. This platform offers a business model of next-generation interaction, which could utilize and digitize the space of the physical world. There are many ideas such as AR experiences, robots or AI agents tasks, digital ads, space monetization etc. --- # 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://zenolab-ai.gitbook.io/story/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.