<?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/e1628942c55d49bebc707e73e3165bc6&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/e1628942c55d49bebc707e73e3165bc6-dff3659417d4411f.gif</thumbnail_url><duration>109.344</duration><title>NASA AI Mission Control in Three Steps</title><description>In this Loom, I explain how NASA uses AI native mission control to fuse multi modal data like radio traffic, drone footage, intelligence reports, and asset locations through voice and natural language. I then layer real time intelligence on top with smart agent recommendations for either human in the loop or autopilot. From one place, you can launch and control a drone or a fleet, task and coordinate them, and monitor results. I also show a quick demo where I click approve to launch and view real time updates.</description></oembed>