Hyper-Scaling Real-Time Personalization with Privacy via On-Device Computing

Explore the challenges and solutions for achieving real-time personalization at scale while maintaining privacy through on-device computing in this 25-minute conference talk from MLOps World: Machine Learning in Production. Delve into the trade-offs between privacy and personalization, latency and throughput, and scale and infrastructure costs. Examine how over-reliance on cloud infrastructure has impacted major applications, affecting revenue streams, complicating deployment cycles, and limiting session-aware ML capabilities. Gain insights into the current state of edge computing infrastructure and discover the future path for MLOps in addressing these challenges.

Hyper-Scaling Real-Time Personalization with Privacy via On-Device Computing