麻豆AV

鈥淎fter an extraordinarily close contest, Google鈥檚 artificially intelligent Go-playing computer system has beaten Lee Sedol, one of the world鈥檚 top players, in the first game of their historic five-game match at Seoul鈥檚 Four Seasons hotel. Known as AlphaGo, this Google creation not only proved it can compete with the game鈥檚 best, but also showed off its remarkable ability to learn the game on its own.鈥� ()

The remaining games can be livestreamed on .

, Professor, School of Computer Science, 麻豆AV

"It is really a historic day for machine learning, especially reinforcement learning. Older large successes, like DeepBlue聽 or Jeopardy, involved significantly more engineering; AlphaGo is truly a learning entity."鈥擠oina Precup

Professor Precup is interested in artificial intelligence and聽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 [dot] mcgill [dot] ca (English, French)

, Professor, School of Computer Science, 麻豆AV

"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. 聽It's exciting to see the pace of progress!聽 Of course we'll be watching closely for the results of the other upcoming games."鈥擩oelle Pineau

Two of the main researchers (Arthur Guez, Marc Lanctot) on Google's聽DeepMind team are alumni of the School of Computer Science at 麻豆AV.聽 Mr. Guez did聽his MSc under Professor聽Pineau's supervision. She co-directs聽the聽.

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 [dot] mcgill [dot] ca (English, French)

, Director, School of Computer Science, 麻豆AV

鈥淭he game of 鈥榞o鈥� is far more complex and challenging for a computer than chess, yet it was only a matter to time before a computer mastered it.聽 For decades games were the standard of performance for emerging artificial intelligence. Those challenges are past and we are in an era聽 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.鈥� 鈥擥regory Dudek

He鈥檚 the Director of聽. He鈥檚 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 [dot] mcgill [dot] ca. 1-514-398-4325. He鈥檚 not available Wednesday between 10-11:45 AM and Thursday, 11:00-11:30 AM. (English, French)