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

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For full show notes and links: https://thehcbiz.com/179-making-machine-learning-available-to-the-masses/