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Machine learning and artificial intelligence are dramatically changing the way businesses operate and people live. The TWIML AI Podcast brings the top minds and ideas from the world of ML and AI to a broad and influential community of ML/AI researchers, data scientists, engineers and tech-savvy business and IT leaders.

Hosted by Sam Charrington, a sought after industry analyst, speaker, commentator and thought leader.

May 16, 2019

Today we’re joined by Genevera Allen, associate professor of statistics in the EECS Department at Rice University, Founder and Director of the Rice Center for Transforming Data to Knowledge and Investigator with the Neurological Research Institute with the Baylor College of Medicine.

Genevera caused quite the stir at the American Association for the Advancement of Science meeting earlier this year with her presentation “Can We Trust Data-Driven Discoveries?" In our conversation we cover:

• The goal of Genevera's talk, and what was lost in translation.

• Use cases outlining the shortcomings of current machine learning techniques.

• Reproducibility, including inference vs discovery, and the lack of terminology for many of the various reproducibility issues, & much more!

The complete show notes for this episode can be found at twimlai.com/talk/266.