Introduction

3min Snip

00:00

Play full episode

Summary

Transcript

Episode notes

The host discusses the lack of a concrete definition for the term 'AI' in engineering and highlights the disturbing update on AI image generators trained on suspected child abuse images. The chapter also introduces Dr. Eric Siegel and his expertise in machine learning and AI.

Dr. Eric Siegel is a leading consultant and former Columbia University professor who helps companies deploy machine learning. He is the founder of the long-running Machine Learning Week conference series and its new sister, Generative AI World, the instructor of the acclaimed online course “Machine Learning Leadership and Practice – End-to-End Mastery,” executive editor of The Machine Learning Times, and a frequent keynote speaker. He wrote the bestselling "Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die," which has been used in courses at hundreds of universities, as well as "The AI Playbook: Mastering the Rare Art of Machine Learning Deployment."

Eric’s interdisciplinary work bridges the stubborn technology/business gap. At Columbia, he won the Distinguished Faculty award when teaching the graduate *computer science* courses in ML and AI. Later, he served as a *business school* professor at UVA Darden. Eric has appeared on numerous media channels, including Bloomberg, National Geographic, and NPR, and has published in Newsweek, HBR, SciAm blog, WaPo, WSJ, and more.

Listen and learn

How he’s progressed in the field of machine learning over 30 years
6-step process to usher in machine learning programs from conception to deployment
What 3 things non-technical people in business should know about how machine learning works & delivers value
How to know when to use classical machine learning vs generative AI to solve a data problem
How to mitigate the impact of human bias in shaping AI

Resources