Simba Khadder

Simba Khadder, founder of Featureform and now at Redis, dives into the fascinating world of context engineering for AI. He argues that context, not models, is the real bottleneck for agents. Simba discusses the evolution of feature stores, emphasizing their ongoing value amidst changing ML economics. He introduces a GraphQL-style semantic layer for better data navigation and details how Redis powers these systems with robust capabilities. Plus, he shares insights on how to improve agent functionality by enhancing context access.

Simba Khadder, Founder and CEO of FeatureForm, shares his expertise in building feature stores and large-scale recommender systems. He discusses the evolution and significance of feature stores in machine learning, the challenges of applying large language models, and innovative data management practices with Iceberg. Simba also reflects on the transformative impact of AI tools on coding and the tension between modern technology and tradition. Plus, he offers insights on surfing as a mindfulness practice, sharing personal stories from his adventures.

Simba Khadder, the founder and CEO of Featureform and a machine learning expert, dives deep into the evolution of feature stores and their intersection with vector stores. He explains the significance of embeddings for recommender systems and discusses how personalization enhances user experiences with large language models. Simba also addresses the challenges in managing feature pipelines and the trade-offs between system complexity and reliability. Tune in to learn about the latest innovations shaping the MLOps landscape!