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Why build your own vector DB? To process 25,000 images per second

Ben and Ryan chat with Babak Behzad, senior engineering manager at Verkada, about running a pipeline that vectorizes 25,000 images per second into a custom-built vector database. They discuss whether the speed is due to technical brains or brawn, the benefits of processing on device vs. off, and the importance of privacy when using image recognition on frames from a video camera.

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Verkada is a cloud-based video security company.

Back in the innocent days of 2021, we spoke with a company that makes smart dashcams. See how far video and image processing has come.

Congrats to Reg for earning a Lifeboat badge for their answer on What is the difference between JSP and Spring?

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