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Ever wondered how robots actually &quot;see&quot; the world? Or why Tesla can achieve so much with just vision?<br><br>I talk with Bradley Dillon, CEO of Luxonis, about how their AI-enabled cameras are becoming the eyes and brains of robots everywhere. Bradley shares how they&#39;ve sold over 150,000 vision platforms and why processing at the edge (right on the camera) is revolutionizing robotics.<br><br>You&#39;ll like this interview if you&#39;re interested in computer vision, edge computing, or how vision technology is making automation possible in industries from agriculture to security screening.<br><br>TRANSCRIPT<br>- https://audrownashpodcast.com/posts/20-luxonis/transcript<br><br>EPISODE LINKS<br>- Luxonis Website: https://www.luxonis.com<br>- Luxonis LinkedIn: https://www.linkedin.com/company/luxonis/<br>- Luxonis X: https://x.com/luxonis<br>- Bradley&#39;s LinkedIn: https://www.linkedin.com/in/bradley-dillon/<br>- Bradley&#39;s X: https://x.com/bradley_luxonis<br><br>PODCAST LINKS<br>- Podcast Website: https://audrownashpodcast.com/<br>- YouTube: https://www.youtube.com/@audrow<br>- Apple Podcasts: https://podcasts.apple.com/us/podcast/audrow-nash-podcast/id1716486786<br>- Spotify: https://open.spotify.com/show/74jWpWiLwsasY2QHtDcl8I?si=6c92796bf9554162<br><br>TIMECODES<br>(0:00) Start<br>(1:52) Bradley Dillon &amp; Luxonis Overview<br>(8:34) Luxonis’s Equipments<br>(13:02) Integrating Multiple Sensors<br>(20:40) Applications of Luxonis Vision<br>(25:02) Luxonis &amp; Computing Power<br>(30:08) Linking Multiple Devices<br>(31:41) Luxonis AI Models<br>(36:31) Data Generation &amp; Labeling<br>(46:25) Future Predictions<br>(50:00) AI for Scene Understanding<br>(59:33) Targeting Industries for Innovation<br>(1:04:54) Smart Security Screening<br>(1:11:46) Growth Story<br>(1:18:58) Chip Supply Challenges<br>(1:26:37) Future Sensor Additions<br>(1:32:45) Luxonis Resources<br>(1:34:53) Outro

Audrow Nash Podcast

Audrow Nash

From Cloud to Edge: Why Vision Processing is Shifting Closer to the Sensor

MAR 13, 202595 MIN
Audrow Nash Podcast

From Cloud to Edge: Why Vision Processing is Shifting Closer to the Sensor

MAR 13, 202595 MIN

Description

Ever wondered how robots actually &quot;see&quot; the world? Or why Tesla can achieve so much with just vision?<br><br>I talk with Bradley Dillon, CEO of Luxonis, about how their AI-enabled cameras are becoming the eyes and brains of robots everywhere. Bradley shares how they&#39;ve sold over 150,000 vision platforms and why processing at the edge (right on the camera) is revolutionizing robotics.<br><br>You&#39;ll like this interview if you&#39;re interested in computer vision, edge computing, or how vision technology is making automation possible in industries from agriculture to security screening.<br><br>TRANSCRIPT<br>- https://audrownashpodcast.com/posts/20-luxonis/transcript<br><br>EPISODE LINKS<br>- Luxonis Website: https://www.luxonis.com<br>- Luxonis LinkedIn: https://www.linkedin.com/company/luxonis/<br>- Luxonis X: https://x.com/luxonis<br>- Bradley&#39;s LinkedIn: https://www.linkedin.com/in/bradley-dillon/<br>- Bradley&#39;s X: https://x.com/bradley_luxonis<br><br>PODCAST LINKS<br>- Podcast Website: https://audrownashpodcast.com/<br>- YouTube: https://www.youtube.com/@audrow<br>- Apple Podcasts: https://podcasts.apple.com/us/podcast/audrow-nash-podcast/id1716486786<br>- Spotify: https://open.spotify.com/show/74jWpWiLwsasY2QHtDcl8I?si=6c92796bf9554162<br><br>TIMECODES<br>(0:00) Start<br>(1:52) Bradley Dillon &amp; Luxonis Overview<br>(8:34) Luxonis’s Equipments<br>(13:02) Integrating Multiple Sensors<br>(20:40) Applications of Luxonis Vision<br>(25:02) Luxonis &amp; Computing Power<br>(30:08) Linking Multiple Devices<br>(31:41) Luxonis AI Models<br>(36:31) Data Generation &amp; Labeling<br>(46:25) Future Predictions<br>(50:00) AI for Scene Understanding<br>(59:33) Targeting Industries for Innovation<br>(1:04:54) Smart Security Screening<br>(1:11:46) Growth Story<br>(1:18:58) Chip Supply Challenges<br>(1:26:37) Future Sensor Additions<br>(1:32:45) Luxonis Resources<br>(1:34:53) Outro