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Pedro Domingos's Interviews
#239 Pedro Domingos Breaks Down The Symbolist Approach to AI
This episode is sponsored by Thuma. Thuma is a modern design company that specializes in timeless home essentials that are mindfully made with premium materials and intentional details. To get $100 towards your first bed purchase, go to http://thuma.co/eyeonai In this episode of the Eye on AI podcast, Pedro Domingo
#237 Pedro Domingo’s on Bayesians and Analogical Learning in AI
This episode is sponsored by Thuma. Thuma is a modern design company that specializes in timeless home essentials that are mindfully made with premium materials and intentional details. To get $100 towards your first bed purchase, go to http://thuma.co/eyeonai In this episode of the Eye on AI podcast, Pedro Domingos,
Longtime machine-learning researcher, and University of Washington Professor Emeritus, Pedro Domingos joins a16z General Partner Martin Casado to discuss the state of artificial intelligence, whether we're really on a path toward AGI, and the value of expressing unpopular opinions. It's a very insightful discussion as
Professor Pedro Domingos, is an AI researcher and professor of computer science. He expresses skepticism about current AI regulation efforts and argues for faster AI development rather than slowing it down. He also discusses the need for new innovations to fulfil the promises of current AI techniques. MLST is sponsored
In this episode, Pedro Domingos - AI - 2040 - Lauren Hawker Zafer is joined by Pedro Domingos. This unique conversation explores AI's impact on politics, particularly in voter targeting and campaign strategies, and the concept of AI as a tool for enhancing collective intelligence. Domingos, with over 200 technical publ
#96 Prof. PEDRO DOMINGOS - There are no infinities, utility functions, neurosymbolic
Pedro Domingos, Professor Emeritus of Computer Science and Engineering at the University of Washington, is renowned for his research in machine learning, particularly for his work on Markov logic networks that allow for uncertain inference. He is also the author of the acclaimed book "The Master Algorithm". Panel: Dr.
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