THE ULTIMATE SOFTWARE: MACHINE LEARNING AND INTELLIGENCE

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Machine learning is the automation of discovery. With it, computers can program themselves instead of having to be programmed by us. Learning systems are widely used in science, business and government, but are still shrouded in mystery. This talk explains the five major paradigms in machine learning – symbolic learning, deep learning, genetic algorithms, Bayesian learning and reasoning by analogy – and samples some of the major applications they enable, from automated biology to personalized recommendations. It concludes with a look at the future: what machine learning will bring us, and the roadblocks, dangers, and opportunities on that path.


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  • Date: 30 Sep 2021
  • Time: 07:00 PM to 08:30 PM
  • All times are (GMT-05:00) US/Eastern
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  Speakers

Dr. Pedro Domingos of University of Washington

Topic:

Machine Learning

Pedro Domingos is a professor of computer science at the University of Washington and the author of "The Master Algorithm". 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 the AAAS and AAAI. His research spans a wide variety of topics in machine learning, artificial intelligence, and data science. He helped start the fields of statistical relational AI, data stream mining, adversarial learning, machine learning for information integration, and influence maximization in social networks.

Biography:

Pedro Domingos is a professor of computer science at the University of Washington and the author of "The Master Algorithm". 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 the AAAS and AAAI. His research spans a wide variety of topics in machine learning, artificial intelligence, and data science. He helped start the fields of statistical relational AI, data stream mining, adversarial learning, machine learning for information integration, and influence maximization in social networks.

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Agenda

7:00 pm - Introductions

7:10 pm - Professor Domingos presentation w/Q&A

8:10 pm - Open Discussion

8:30 pm - Close