Real-Time Fine-Tuning of Embedding Models for Improved Retrieval with Hopsworks and Bytewax

Continuous embedding model optimization is crucial for enhancing retrieval accuracy and relevance in dynamic environments. This approach allows AI systems to adapt in real-time to evolving data and interactions, providing significant benefits including personalized content recommendation, dynamic search engines, real-time fraud detection and social media monitoring.

Participants will learn how to implement continuous embedding model optimization using Hopsworks and Bytewax, focusing on real-time fine-tuning to improve retrieval performance across these diverse applications.