2018MIT課程：通用人工智慧
This class takes an engineering approach to exploring possible research paths toward building human-level intelligence. The lectures will introduce our current understanding of computational intelligence and ways in which strong AI could possibly be achieved, with insights from deep learning, reinforcement learning, computational neuroscience, robotics, cognitive modeling, psychology, and more. Additional topics will include AI safety and ethics. Projects will seek to build intuition about the limitations of state-of-the-art machine learning approaches and how those limitations may be overcome. The course will include several guest talks. Listeners are welcome.
課程地址：https://agi.mit.edu/
2018 Schedule of Lectures and Talks
Most (but not all) lectures and talks will be at 7pm inRoom 54-100. See below for exact time and location.
1.LectureMon, Jan 22, 7pmRoom 54-100
Artificial General Intelligence
[ Slides ] - [ Lecture Video ](Available Soon)
2.Guest TalkTue, Jan 23, 7pmRoom 54-100
Josh Tenenbaum: Computational Cognitive Science
Professor, MIT
3.Guest TalkWed, Jan 24, 1pmRoom 10-250
Ray Kurzweil: How to Create a Mind
4.Guest TalkThu, Jan 25, 7pmRoom 54-100
Lisa Feldman Barrett: Emotion Creation
Northeastern University
5.Guest TalkFri, Jan 26, 7pmRoom 54-100
Nate Derbinsky: Cognitive Modeling
Northeastern University
6.Guest TalkMon, Jan 29, 1pmRoom 26-100
Andrej Karpathy: Deep Learning
Director of AI, Tesla
Previously: OpenAI, Stanford University
7.LectureTue, Jan 20, 7pmRoom 54-100
Turing Test and Beyond
[ Slides ] - [ Lecture Video ](Available Soon)
8.Guest TalkWed, Jan 31, 7pmRoom 54-100
Mark Reibert: Robotics
CEO, Boston Dynamics
Previously: MIT
9.Guest TalkThu, Feb 1, 7pmRoom 54-100
Ilya Sutskever: Deep Reinforcement Learning
Co-founder, OpenAI
Previously: Google Brain, Stanford, U of Toronto
10.LectureMon, Jan 22, 7pmRoom 54-100
Human-Centered Artificial Intelligence
[ Slides ] - [ Lecture Video ](Available Soon)
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