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The Stack Overflow Podcast

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

Feb 7, 2025
Babak Bezad, Senior Engineering Manager at Verkada, dives into the cutting-edge realm of AI and image processing in video security. He shares insights on creating vector embeddings to handle massive data, utilizing technologies like YOLO and CLIP. The conversation explores the complexities of building a privacy-focused AI cloud and the importance of consumer control over features. Bezad highlights advancements in real-time anomaly detection and the integration of AI models to boost image processing accuracy, showcasing the future of security technology.
35:20

Episode guests

Podcast summary created with Snipd AI

Quick takeaways

  • Verkata's development of an in-house vector database is driven by the need for privacy and scalability, allowing secure management of sensitive image data.
  • The integration of AI in Verkata's security systems enhances object detection and search capabilities, enabling rapid, precise visual data retrieval for various clients.

Deep dives

Future of AI in Security

The podcast discusses the increasing role of AI in video security, particularly focusing on Verkata's solutions which emphasize privacy and safety. Verkata's mission revolves around protecting people and places through advanced cloud-based security systems, serving a diverse range of customers, including gyms, schools, hospitals, and retail stores. The company utilizes over a million cameras globally, leveraging capabilities like object detection to minimize data transmission and provide rapid analytical insights. As AI technologies evolve, there is a strong emphasis on creating more intelligent security cameras that can recognize threats in real time, paving the way for a more proactive approach to safety.

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