
Pedro Domingos, "The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World" (Basic Books, 2018)
From New Books in Technology by New Books Network
May 30, 2026 · 1h 11m
About this episode
Pedro Domingos discusses his book on the quest for the ultimate learning algorithm and its implications for the future.
In the world's top research labs and universities, the race is on to invent the ultimate learning algorithm: one capable of discovering any knowledge from data, and doing anything we want, before we even ask. In The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World (Basic Books, 2018), Pedro Domingos lifts the veil to give us a peek inside the learning machines that power Google, Amazon, and your smartphone. He assembles a blueprint for the future universal learner--the Master Algorithm--and discusses what it will mean for business, science, and society. If data-ism is today's philosophy, this book is its bible. Pedro Domingos is a professor emeritus of computer science at the University of Washington. He is a winner of the SIGKDD Innovation Award, the highest honor in data science. A fellow of the Association for the Advancement of Artificial Intelligence, he lives near Seattle. Gregory McNiff is a Managing Director in the New York office of the Blueshirt Group, an IR firm focused on technology; he has a strong interest in literature, culture, religion, science and philosophy (translation: he's an eclectic reader who is constantly missing…
People in this episode
Host: Gregory McNiff
Guest: Pedro Domingos
Topics covered
- machine learning
- artificial intelligence
- data science
- technology
- business
- society
Keywords
- learning algorithm
- data-ism
- universal learner
- Amazon
- smartphone
- SIGKDD Innovation Award
- artificial intelligence
Mentioned in this episode
Organizations: University of Washington, Blueshirt Group, Basic Books
Books & works: The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World
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