<?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/8413cd210cb64dd1837e6442341f00a6&quot; frameborder=&quot;0&quot; width=&quot;1728&quot; height=&quot;1296&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1296</height><width>1728</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1296</thumbnail_height><thumbnail_width>1728</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/8413cd210cb64dd1837e6442341f00a6-529c76298181ac00.gif</thumbnail_url><duration>296.214</duration><title>Revolutionizing Crop Disease Detection with Apollo AI</title><description>Hi there, I&apos;m Rusan from Apollo AI, and in this video, I explain our project aimed at addressing crop diseases that cost the global economy around $220 billion each year. Traditional lab analyses take about three days, which is too slow for fast-developing diseases, so we&apos;re working to speed up this process with our plant diagnostics model. I demonstrate our AI&apos;s ability to detect diseases in plants with a confidence rate of 100% using a dataset of over 70,000 images. We&apos;re currently in the MVP stage and plan to expand our capabilities to include thermal detection in the future. I encourage you to watch the demo and share your thoughts on our progress.</description></oembed>