Saturday, September 10, 2011


It's a new school year!  Remember the first day of school?  Nothing beats that feeling of new notebooks and overwhelmed freshmen.  It's times like this that I love the east coast, and Cambridge in particular.  This is the center of the world for education and you can feel everyone getting ready for the new semester.  In the past I've limited the amount of non-research things I did, but I decided this semester I would take classes in anything I found interesting, regardless of how it connects to my work.  So far I've tried out six classes (about five too many):

6.893, Philosophy and Theoretical Computer Science, taught by Scott Aaronson.  I am *really* excited about this class!  I tried taking philosophy classes in undergrad and got really turned off, but I like the idea of approaching it from TCS.  In theory we rarely get to ask what this stuff really *means* and what its implications are to what can be done or known in the world, and I like the idea of indulging in that.  It's 3 hours a week of interesting reading and discussion, and it looks like Scott is going to record lectures, so you can listen in!

9.29, Introduction to Computational Neuroscience and 6.804 Computational Cognitive Science, taught by Michale Fee and Josh Tenenbaum, respectively.  People who study brains and AI here at MIT are starting to ask the big questions again -- there's a new Intelligence Initiative, bringing together people from neuroscience, cognitive science, computer science, economics, and biology to get at how intelligence works.  So interesting!  My background in physics and statistics is pretty terrible, so I don't think I'm going to take these classes for credit, though it's nice to learn a new vocabulary and see how other fields operate.

9.S915, What is Intelligence?  Are you seeing a theme here?  This course meets once a week and does a huge survey over all the areas mentioned above -- I'm skeptical about how valuable it will be, in the first class we spent two hours going over statistical learning theory really, really fast.  I still have no idea how to make a good learning algorithm.

6.853, Topics in Algorithmic Game Theory, taught by Costis.  I miss math soooo much, and I find game theory pretty fascinating -- in fact I wrote my NSF planned research essay on game theory, but then proceeded to do something completely different.  I'd like to think about applying game theory to security! There's a pretty cool systems security class being taught this semester too, but I think I might have picked up a lot of what's being taught in my past research.

After a long summer of trying to do one thing and not being very effective, I'm really excited to take classes, go to colloquia, and in general try lots of new things this semester.  It's funny how trying to force one project can be demotivating, devolving into a cycle of trying to work harder/getting less done.  One of my goals this year is to learn to work in a very minimal, effective way.  Last summer I remember being so sad when the days started getting colder, but this year I can't wait for fall.  It's seriously the best season ever (and we need something to brag about weather-wise on the east coast):

  • trees exploding in color and crunchy leaves everywhere
  • apple picking, apple pies, apple cider, and cinnamon in everything
  • cozy sweaters and corduroy
  • crisp mornings where you can see the steam on your coffee
  • scarves
  • the feeling of starting over you get with the new school year
It's funny, I'm actually starting to feel like I'm in the right place.  I've spent three years here unclear on what I was doing and worrying that I was missing the boat on other things -- being able to program and create products is a huge privilege and I worried I was wasting it.  I believe technology (in particular software and the internet) is the fastest, most powerful source of transformation we can harness, but the thought of spending my time on a local-mobile-game-coupon thing never seemed inspiring.  

So far I feel good about what I'm doing this semester.  It feels nice.


  • cider doughnuts
  • boots
  • new coats
  • PUMPKINS (in all forms: pumpkin beer, pumpkin bread, pumpkin pie, pumpkin chai)