Improving your AI by finding issues within data pockets (Ep. 195)

from Data Science at Home · host Francesco Gadaleta <frag>

In this episode I have a conversation with, Itai Bar-Sinai, CPO & Cofounder of Mona. We speak about several interesting points about data and monitoring.Why is AI monitoring so different from monitoring classic software?How to reduce the gap between data science and business?What is the role of MLOps in the data monitoring field?With over 10 years of experience with AI and as the CPO and head of customer success at Mona, the leading AI monitoring intelligence company, Itai has a unique view of the AI industry. Working closely with data science and ML teams applying dozens of AI solutions in over 10 industries, Itai encounters the wide variety of business use-cases, organizational structures and cultures, and technologies and tools used in today’s AI world. Referenceshttps://www.monalabs.io This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit datascienceathome.substack.com

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