The Joe Reis Show
Simba Khadder - Feature Stores, Reinforcement Learning, and More
Jan 2, 2025
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.
52:18
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Quick takeaways
- Feature stores are evolving as essential components in machine learning, promoting better data management and integration into workflows.
- Organizations are balancing the use of traditional machine learning models alongside advanced techniques like LLMs to enhance performance and value.
Deep dives
The Evolution of Feature Stores
Feature stores have become a vital part of the machine learning landscape, evolving out of the need for better data management in machine learning processes. Initially, many organizations found that machine learning was more data-driven than model-based, leading to confusion and varying approaches among different vendors. Some companies opted for traditional feature storage as tables, while others focused on defining features as code and building pipelines. Over time, the narrative around feature stores has shifted, moving from hype to a sustainable growth phase, with companies now acknowledging the importance of established practices for better integration into their workflows.
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