“After an extraordinarily close contest, Google’s artificially intelligent Go-playing computer system has beaten Lee Sedol, one of the world’s top players, in the first game of their historic five-game match at Seoul’s Four Seasons hotel. Known as AlphaGo, this Google creation not only proved it can compete with the game’s best, but also showed off its remarkable ability to learn the game on its own.” (Wired)
The remaining games can be livestreamed on DeepMind YouTube channel.
Doina Precup, Professor, School of Computer Science, McGill University
"It is really a historic day for machine learning, especially reinforcement learning. Older large successes, like DeepBlue or Jeopardy, involved significantly more engineering; AlphaGo is truly a learning entity."—Doina Precup
Professor Precup is interested in artificial intelligence and machine learning.
She's not available today between 11:00 AM - 12:00 PM and 2:30-3:30 PM. She's not available tomorrow between 10 AM - 11:30 AM.
dprecup [at] cs.mcgill.ca (English, French)
Joelle Pineau, Professor, School of Computer Science, McGill University
"The game of Go has been a milestone for AI researchers for several years. Many people thought we would not attain human-level performance for another decade. It's exciting to see the pace of progress! Of course we'll be watching closely for the results of the other upcoming games."—Joelle Pineau
Two of the main researchers (Arthur Guez, Marc Lanctot) on Google's DeepMind team are alumni of the School of Computer Science at McGill. Mr. Guez did his MSc under Professor Pineau's supervision. She co-directs the Reasoning and Learning Lab.
She's available today between 1:30-2 PM and 3:30-4 PM today. Tomorrow, between 1-2:30 PM. Friday, between 10:30-11 AM.
jpineau [at] cs.mcgill.ca (English, French)
Gregory Dudek, Director, School of Computer Science, McGill University
“The game of ‘go’ is far more complex and challenging for a computer than chess, yet it was only a matter to time before a computer mastered it. For decades games were the standard of performance for emerging artificial intelligence. Those challenges are past and we are in an era when robotics and intelligent machines will gradually meet and surpass any remaining reasonable intellectual challenge we can propose. This success is especially striking since it exemplified a new class of solution that is much closer to how humans plan this and other games.” —Gregory Dudek
He’s the Director of NSERC Canadian Field Robotics Network (NCFRN). He’s interested in robot navigation, mobile robotics, robot localization, information summarization, human-robot interaction, sensor-based robotics, multi-robot systems, computer vision, vision, recommender system, web services, recognition.
dudek [at] cim.mcgill.ca. 1-514-398-4325. He’s not available Wednesday between 10-11:45 AM and Thursday, 11:00-11:30 AM. (English, French)