From the course: Using Spatial Data in AI Workflows
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Role of AI in map-based applications
From the course: Using Spatial Data in AI Workflows
Role of AI in map-based applications
We are all used to map applications. Whether it's Google Maps or a dashboard at work, the interaction is almost always the same. You pan, you zoom, you click a filter, you toggle a checkbox. If you want to find large airports in the United States, you have to know exactly which buttons to press. You have to translate your intent into clicks. But with LLMs integrated into the map experience, we can invert this. Instead of you learning the interface, The interface learns you. In this section, we are going to build an AI-controlled map application. We call this pattern front-end-first AI. Unlike our previous projects, there is no Python back-end. There's no database server. Everything happens right in the browser. Let's take a look at the architecture we are building. First, we have the application layer. This is a simple, standard web app built with HTML, CSS, and JavaScript. Second, we have the map engine. We're using map-libre-gl.js, a powerful open source library that renders maps…
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