<?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/a063199b8c6d4bd38afb6b6aaee0eb0f&quot; frameborder=&quot;0&quot; width=&quot;1670&quot; height=&quot;1252&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1252</height><width>1670</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1252</thumbnail_height><thumbnail_width>1670</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/a063199b8c6d4bd38afb6b6aaee0eb0f-bd47798a10e8b62b.gif</thumbnail_url><duration>92.494</duration><title>Enhancing AI Interactions with Contextual Memory 🚀</title><description>In this video, I discuss our project aimed at enhancing user interactions by allowing us to repeat previous tasks more efficiently. We have developed a front end that connects to user sessions, storing context and chat messages in a database. Our knowledge exchange engine utilizes user actions and past knowledge to implement tasks, with GTP5 assisting in rewriting and appending messages. I encourage everyone to think about how we can leverage this system to improve our workflows. Please share any thoughts or feedback on this approach.</description></oembed>