Wednesday, November 16, 2011

Stanford AI Class

During the past few weeks I've been following the video lectures that Sebastian Thrun and Peter Norvig post every week, and that constitute their "Introduction to Artificial Intelligence" course.

I have to say that I love the course. Even if, as an AI researcher, I should know everything that they explain, it's nice to hear it again properly summarized and explained. What is more interesting about this course is that, given it's crazy amount of students (I've heard the count is about 160000!), it's generating lots of reactions among AI researchers. Some people love it, some people hate it. Here's my take on it.

I agree with many that the course is extremely biased (specially the machine learning part), and that only those techniques coming from probability and statistics are covered in the course. For example, the supervised learning module basically covers Bayesian learning, linear regression and nearest neighbor (and this last one is a nice addition!). This leaves out all the "search-based" machine learning methods (based on the idea of searching in a hypothesis space) like: version spaces or decision trees. This is an "introduction to AI" class, and I understand that they leave out the more fashionable topics like kernel methods. But I think that the search-based approach to machine learning deserves a module in this course. Whole fields (like inductive logic programming) come from this tradition of machine learning.

The same happens with the planning module of the course. Traditional introductory courses to AI use STRIPS planning to introduce the students to the idea of planning, and only tangentially touch on the problem of planning under uncertainty. However, this course does the opposite. Which is kind of weird. But here I don't have such a strong opinion as with the machine learning module.

Given the large number of students, and the strong bias of the course. Several AI researchers are actually angry at the course, since it's shaping the mind of a whole generation of potential AI researchers.

That said, I still think the course is awesome, and I follow it every week.

And I say this: all of those (and I include myself) who disagree with the way Sebastian and Peter teach their course should, instead of complain, just try to follow their lead and create an online course that represents their view of AI. Maybe we could even create a youtube channel for "missing lectures from the Stanford intro to AI course" :)