And What You Can Take from Each Pedro Domingos University of Washington ACM Highlights • Learning Center tools for professional development: http://learning.acm.org • 4,000+ trusted technical books and videos by O’Reilly, Morgan Kaufmann, etc. • 1,000+ courses, virtual labs, test preps, live mentoring for software professionals covering programming, data management, cybersecurity, networking, project management, more • Training toward top vendor certifications (CEH, Cisco, CISSP, CompTIA, ITIL, PMI, etc.) • Learning Webinars from thought leaders and top practitioner • Podcast interviews with innovators, entrepreneurs, and award winners • Popular publications: • Flagship Communications of the ACM (CACM) magazine: http://cacm.acm.org/ • ACM Queue magazine for practitioners: http://queue.acm.org/ • ACM Digital Library, the world’s most comprehensive database of computing literature: http://dl.acm.org. • International conferences that draw leading experts on a broad spectrum of computing topics: http://www.acm.org/conferences. • Prestigious awards, including the ACM A.M. Turing and Infosys: http://awards.acm.org • And much more… http://www.acm.org. Talk Back • Use Twitter widget to Tweet your favorite quotes from today’s presentation with hashtag #ACMLearning • Submit questions and comments via Twitter to @acmeducation – we’re reading them! • Use the sharing widget in the bottom panel to share this presentation with friends and colleagues. Evolution Culture Experience Evolution Experience Culture Computers Most of the knowledge in the world in the future is going to be extracted by machines and will reside in machines. – Yann LeCun, Director of AI Research, Facebook 1. Fill in gaps in existing knowledge 2. Emulate the brain 3. Simulate evolution 4. Systematically reduce uncertainty 5. Notice similarities between old and new Tribe Origins Master Algorithm Symbolists Logic, philosophy Inverse deduction Connectionists Neuroscience Backpropagation Evolutionaries Evolutionary biology Genetic programming Bayesians Statistics Probabilistic inference Analogizers Psychology Kernel machines Tom Mitchell Steve Muggleton Ross Quinlan Addition Subtraction 2 + 2 ――― ―― = ? 2 + ? ――― ―― = 4 Deduction Induction Socrates is human + Humans are mortal . ――――――――――― ―――――――――― ? = Socrates is human ? + ――――――――――― ―――――――――― = Socrates is mortal Yann LeCun Geoff Hinton Yoshua Bengio John Koza John Holland Hod Lipson David Heckerman Judea Pearl Michael Jordan Peter Hart Vladimir Vapnik Douglas Hofstadter Tribe Problem Solution Symbolists Knowledge composition Inverse deduction Connectionists Credit assignment Backpropagation Evolutionaries Structure discovery Genetic programming Bayesians Uncertainty Probabilistic inference Analogizers Similarity Kernel machines Tribe Problem Solution Symbolists Knowledge composition Inverse deduction Connectionists Credit assignment Backpropagation Evolutionaries Structure discovery Genetic programming Bayesians Uncertainty Probabilistic inference Analogizers Similarity Kernel machines But what we really need is a single algorithm that solves all five! Representation Probabilistic logic (e.g., Markov logic networks) Weighted formulas → Distribution over states Evaluation Posterior probability User-defined objective function Optimization Formula discovery: Genetic programming Weight learning: Backpropagation Much remains to be done . . . We need your ideas Home Robots World Wide Brains Cancer Cures 360o Recommenders If we used all our technology resources, we could actually give people personalized recommendations for every step of your life. – Aneesh Chopra, former CTO of the U.S. ACM: The Learning Continues… Questions about this webcast? learning@acm.org ACM Learning Webinars (on-demand archive): http://learning.acm.org/webinar ACM Learning Center: http://learning.acm.org ACM SIGKDD: http://www.kdd.org/ ACM Queue: http://queue.acm.org/