2018MIT课程：通用人工智能

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.

课程地址：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

Google

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)