In this talk, Aparna Dhinakaran, Founder of Arize AI (Ex-Uber ML), will highlight common model failure modes including model drift, data quality issues, performance degradation, etc. The talk will also surface how ML Observability can address these challenges by monitoring for failures, providing tools to troubleshoot and identify the root cause, as well as playing an important part in the feedback loop to improving models. The talk will highlight best practices and share examples from across the industry.
FEATURED TALK (AI): ML Observability: A Critical Piece in Making Models Work
Aparna Dhinakaran is Chief Product Officer at Arize AI; a startup focused on ML Observability. She was previously an ML engineer at Uber, Apple, and Tubemogul (acquired by Adobe). During her time at Uber, she built several core ML Infrastructure platforms, including Michaelangelo. She has a bachelor’s from Berkeley's Electrical Engineering and Computer Science program, where she published research with Berkeley's AI Research group. She is on a leave of absence from the Computer Vision Ph.D. program at Cornell University.