We talk about ML and AI quite a bit on this show. Our angle is always to avoid the hype and help you find the practical applications that you can put to work right now. Today's episode is a great extension of this ongoing conversation. We talk with Dr. Taha Kass-Hout, Chief Medical Officer and Director, Machine Learning at Amazon Web Services about how they are trying to bring ML to the masses. We discuss: What's needed to use machine learning at scale with cost efficiency, performance, and accountability. The challenges in analyzing healthcare's largely unstructured data. The practicality of bringing AI/ML capabilities directly to the hospitals, health systems, medical offices, etc. How should CIOs and other buyers evaluate ML solutions? How can they tell what is real and what is hype? Detecting bias, drift in models, and drift in data in machine learning. Tooling for privacy, security, and compliance. The importance of owning and controlling your own data. The problems caused by bad training data ... For full show notes and links: https://thehcbiz.com/179-making-machine-learning-available-to-the-masses/

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