The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) The New DBfication of ML/AI with Arun Kumar - #553
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Jan 17, 2022 
In this engaging conversation, Arun Kumar, an associate professor at UC San Diego known for his work on Cerebro and SortingHat, discusses the exciting concept of 'DBfication' in machine learning. He emphasizes how merging ML and database technologies can enhance efficiency and scalability. Arun shares insights on his innovative tools, Cerebro for optimal model selection and SortingHat for automating data prep. Their integration could significantly improve machine learning workflows, showcasing the future potential of MLOps and collaborative efforts in both fields.
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DBfication of ML/AI
- Arun Kumar coined "DBfication" to describe the integration of database principles into ML/AI.
- This mirrors how relational databases evolved, addressing scalability, manageability, and usability.
Evolution of ML Platforms
- In-RDBMS ML toolkits demonstrate the early stages of merging databases and ML.
- Modern ML platforms need to expand beyond just training and inference, addressing governance and data transformations.
Democratizing ML
- ML/AI has transitioned from an academic pursuit to a business-critical need.
- Democratizing ML requires tackling usability and scalability challenges for both humans and systems.