Emeritus Lecture: Pedro Domingos (Oct 2022)

Machine Learning: The Last 20 Years and the Next
Pedro Domingos (Emeritus - University of Washington)
Abstract
The last 20 years were eventful ones in machine learning, and the Allen School played a big part. In this talk I will briefly look at seven fields we helped start or grow: massive-scale learning, adversarial learning, influence maximization in social networks, machine learning for data integration, statistical relational learning, symmetry-based learning, and deep learning. In each case I will tell the story of how it came about, summarize the main results, and lay out today's challenges and research frontiers. I will also touch on how we helped develop machine learning education and popularize it into the technological, economic and cultural force it is today, and speculate on where it might be headed.
Bio
Pedro Domingos is Professor Emeritus of Computer Science & Engineering at the University of Washington's Allen School, and the author of The Master Algorithm, the worldwide bestseller introducing machine learning to a broad audience. He is a winner of the SIGKDD Innovation Award and the IJCAI John McCarthy Award, two of the highest honors in data science and AI, and a Fellow of AAAS and AAAI. His papers and systems have won ten awards at major AI conferences. He co-founded the International Machine Learning Society in 2001.
This lecture was originally given on October 20, 2022.
This video is close captioned.

[@ChannelYourDenovations]

I'm a few chapters into the "Master Algorithm" book. The book is old but I find starting from the basics definitely helps with a starting point and looking at where we are now. Right now, I'm trying to build a simple chatbot through python that learns from the user. The purpose of this chatbot will be to help me with my studies. So, essentially I'm trying to program a self-tutor tailored specifically to me. But this is a far cry from any Master Algorithm. Yet, it's a fist step. I don't think you need to be a genius to help. You just need a drive and some will to learn.

[@stevehaas9515]

Everyone is looking for AI knowledge. Yet no one is commenting on this video by the leading expert. Odd.

[@hirmor666]

True. One of my favorite experts in the field.

[@alexsmith8536]

brother still using the same "friends x smoking" example for the past 17 years. WHERE ARE THE REAL LIFE EXAMPLES? As in examples from bioinformatics, cancer research etc? These toy examples and models you provide only go so far. They are good to illustrate a point but essentially unaplicable to anything past the complexity they describe.