So many pages...
1,321 karma · joined August 3, 2010
Google, Cisco, Kiva, HP, Sun Microsystems, Theranos, Yahoo, Trulia, StubHub, Lytro, Coursera, Bonobos, Snapchat, and Instagram came out of Stanford in one way or another. These companies showcase a diverse range of tech that IS useful.
It's unfair too to say that social media doesn't do anything useful. Facebook reports 1.4 billion MAUs and works to bring the internet to more and more corners of the world. Snapchat's social component has given it the platform on which to innovate.
True, many Stanford students are already wealthy. True, there's a recent trend toward social media companies. But, Stanford continues to be a place where students work incredibly hard and remain motivated to do impactful work. Stanford has a storied history of entrepreneurship that begins before Snapchat and will continue after it.
1) The current tech boom. There's the perception of being able to easily create a startup or to get a programming job at a tech company. Some major in computer science also for the technical skills it gives even though they plan not to pursue programming as a job. They may want to become a PM, or a related non day-to-day programming role for which understanding technical concepts is important.
2) Financial downturn of 08. Many students who would have previously majored in economics or finance have chosen computer science due to the folding of many investment banks as well as the increasing negative perception of working on Wall Street.
3) Increase in diversity of the major. The major has become more interdisciplinary. You used to be required to take very "hardcore" classes like operating systems and compilers. Now though with the rise of fields like HCI the major has become more diverse.
4) Social tipping-point. There is a common joke at Stanford that everyone is a CS major. More people majoring in CS means more help from peers who have been through the same classes and can help out. This social support leads to the positive feedback loop of more people entering the major.
Really cool idea. Great work. I love to see this kind of stuff.
One interesting happening I've noticed too is that with mathematical and computing knowledge specifically it seems that as people gain knowledge it becomes easier to add new knowledge. The curve seems exponential. It's easy to pick up Python if you're already familiar with C and C++. It's easy to understand a new comparison sorting algorithm if you know it can't be faster than O(n lg n) and can place it in perspective with merge and quicksort.
This is why I still go on Stack Overflow and am floored by how few questions I can answer and how much more experienced guys know than me. But I have hope that learning will beget faster learning.
There are a number of other reasons I would argue though for the skyrocketing enrollment in CS here:
First, the financial meltdown has prompted a lot of kids that would have majored in things like economics or management science to get into CS.
Second, the introductory CS classes are widely considered some of the best classes here. The CS department has taken the time to hire a group of phenomenal lecturers who love what they do and who spent an incredible amount of time crafting these classes.
Third, the introductory classes offer a level of human-to-human support that is unprecedented in any other department. We use undergraduate TA's (like myself) for the intro classes. We are a lot cheaper and so there are a lot more of us than there could be graduate TA's. For example, the computer LaIR is staffed with TA's from 6pm - midnight Sunday through Thursday.
Fourth, the CS department dropped the CS140 requirement (hardcore operating systems -- the "dump your girlfriend/boyfriend before you take this class because you won't be together after" class) in favor of two more gentler systems courses. This was mostly the result of the widening breadth of subject matter in CS and requirements that the department felt did not keep up with the offerings.
Fifth, CS itself has become an incredibly diverse subject. Here there are seven concentrations within the major: artificial intelligence, theory, graphics, information, systems, biocomputation, and human-computer interaction. There is a lot of overlap between them, but those overlaps also allow students to reach into other departments to get CS credit that they wouldn't have gotten within the department (e.g. art classes, physics, bio, etc). One of my friends who is concentrating in HCI is taking all studio art this quarter.
Sixth, and perhaps most importantly, computing is becoming the platform on which a lot of other disciplines are built. It is becoming a fundamental tool, in my opinion. Look at computational linguistics and bioinformatics. Even writing papers now comes down to understanding computers... I mean, after programming a lot, you get pretty darn good at Googling, a nontrivial skill I would argue.
Ok, maybe this should have been posted as a general comment, but I'll leave it here for contextual reasons.
One thing you guys might be interested in: https://courseware.stanford.edu/pg/concept_map/index/41601 Daphne Koller is a Stanford CS professor who has been teaching her course CS228 on Probabilistic Models in a similar format for a couple of years. She has the lectures online by chunks of about 10 minutes and then uses in-class time for more interactive sessions. (I'm not sure if you can access the videos if you don't have a Stanford login though)
I really think this method of learning makes so much sense for any level student. Can't wait to see it progress!
I find the exercise dashboard kind of strange. Is math the only available subject? And do you have to go through all the prerequisite exercises to progress to the next ones?
You don't hear the student bragging about how he got enough sleep last night and got all of his work done ahead of time.
I'm an undergrad at Stanford and I think that if you plan ahead well enough it isn't difficult to get enough sleep and get all your work done. It's not only about managing time during the term, but also about managing which classes you take together term-to-term.
There is also something to be said for developing endurance. Eventually you're going to have to do something you don't want to do while incredibly tired.. so pulling all-nighters is a kind of training for that.
I think the general argument is that Germany and China both run huge current account surpluses. China accomplishes this partly through structural regulations and by holding the yuan at an undervalued rate. Germany, on the other hand, cut taxes and reformed its labor and welfare systems in the mid-2000's but in a way that prevents the system from equalizing. The main reason the author gives is that wages don't rise because workers are willing to accept reduced pay raises for job security.
"We know that people will keep trying: attempts to game Google’s ranking, like the ones mentioned in the article, go on 24 hours a day, every single day. That’s why we cannot reveal the details of our solution—the underlying signals, data sources, and how we combined them to improve our rankings—beyond what we’ve already said."
Doesn't this sound like the exact things security people used to say before realizing that they needed to make their mechanisms public in order to ensure their security.