<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/6c715563b8ec45f280213e5466f0be14&quot; frameborder=&quot;0&quot; width=&quot;1920&quot; height=&quot;1440&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1440</height><width>1920</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1440</thumbnail_height><thumbnail_width>1920</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/6c715563b8ec45f280213e5466f0be14-00001.gif</thumbnail_url><duration>300.119</duration><title>Building Memory for AI Applications 🧠</title><description>In this video, I introduce a personal graph library for AI applications that tackles long-term memory challenges in AI systems. The library allows users to create, manage, and query knowledge graphs, supporting natural language queries and local database storage. I demonstrate examples of converting text to graphs, storing user interactions, and querying knowledge graphs. Viewers are encouraged to explore the functionalities showcased.</description></oembed>