|Time:||Wednesdays at 4:30|
|Organizers:||Tony Fader and Abe Friesen|
This quarter's 590a seminar is going to be a series of discussions and talks about big debates, successes, and failures in the history of AI. Our primary goal is to get students excited about their work by giving them a historical perspective on current research in AI.
We'll be discussing topics like these:
Each week, a disucssion leader will pick a topic and find some good reading material. They'll be responsible for summarizing the topic (10-15 minutes) and moderating a discussion. To keep things informal, the discussion leader should come equipped with questions and talking points, but no slides.
|January 9||Tony and Abe||
The Chomsky-Norvig Debate: What is the role of statistics in AI?
Some other useful links:
|January 16||Rob Gens||
A nice overview:
Deep Learning Architectures for AI by Yoshua Bengio.
The "cat face" paper from Jeff Dean and Andrew Ng.
Building High-level Features Using Large Scale Unsupervised Learning
Some recent press:
A blog post talking about why deep belief networks make less sense for language than vision.
|January 23||Morgan Dixon||
AI vs. HCI punchout
Direct manipulation vs. interface agents by Ben Shneiderman and Pattie Maes.
Some other readings from Morgan:
|January 30||Adam Smith||
Discovery Systems and the Automation of Science |
Computational Approaches to Scientific Discovery - Jeff Shrager and Patt Langley from 1990.
Why AM and Eurisko Appear to Work - Douglas B. Lenat and John Seeley Brown, 1983.
Other readings from Adam:
|February 6||Cynthia Matuszek||
The Cyc Project
Cyc: Toward Programs with Common Sense - Douglas B. Lenat, Ramanathan V Guha, Karen Pittman, Dexter Pratt, and Mary Shepherd. 1990.
Cynthia also sent out these links:
|February 13||Richard Newcombe||
Intelligence Without Representation - Rodney A. Brooks, 1987.
More materials from Richard:
|February 20||Dan Butler||
Reasoning with Cause and Effect - Judea Pearl, 1999.
Additional reading/watching from Dan:
|February 27||Abe-n-Tony||The Unreasonable Effectiveness of Data by Alon Halevy, Peter Norvig, and Fernando Pereira.|
Is machine learning getting us to artificial intelligence?
Bite-sized blog post from Andrew Gelman and main paper by Duvenaud, Lloyd, Grosse, Tenenbaum, and Ghahramani, 2013.
|March 13||John Doe-Smith||What Is a Knowledge Representation? by Davis, Shrobe, and Szolovits, 1993.|
Here are some suggestsions for discussion topics, as well as resources to where good topics may be lurking.