How Wyze Uses AI to Scale Cost-Efficient Video Understanding
Since its founding in 2017, Wyze has become a leading force in the smart home industry, delivering over 30 million AI-powered devices to more than 10 million households across the U.S. Every day, Wyze's AI infrastructure ingests and processes billions of video events - presenting enormous challenges in secure, accurate, and cost-efficient video processing at scale.
In this talk, we will explore how Wyze AI is tackling these challenges across multiple dimensions.
Edge-to-Cloud Video Processing: Strategies for efficiently distributing and processing high-volume camera footage between on-device and cloud systems.
Deep learning based AI detection: How earlier generations of AI have been successfully deployed to provide powerful person, pet, package, and vehicle detection (PPPVF) features at low cost to customers.
LLM enhanced video understanding: How the latest advancements in large language and vision-language models (LLMs and VLMs) are enabling semantic video search, deeper event understanding, and enhanced customer experiences.
This session will offer a deep dive into how Wyze is building one of the largest and most intelligent smart home video platforms in the U.S., highlighting the practical AI innovations that are shaping the future of home security, automation, and user experience.

Adam Brown
Co-Founder & CTO
Mux
Adam Brown co-founded Mux in 2015 and leads technology and architecture for the developer-first video infrastructure platform. With deep roots in video technology, Adam has built high-performance encoding systems, low‑latency live streaming pipelines, and scalable cloud video infrastructure, including during his time at Zencoder and Brightcove, with additional experience in VR rendering at Otoy.
Known for merging engineering rigor with developer empathy, he’s focused on enabling seamless, scalable video delivery and real-time analytics through API-first products like Mux Video and Mux Data.