"Pen Science" is to Writing as CS is to Web 2.0
Do you agree with this analogy?
EDIT: Looking back at the topic, I'm not sure if the submitter is aware of Dijkstra's comment about the nature of Computer Science: "Computer Science is no more about computers than astronomy is about telescopes". Comparing Computer Science to "Pen Science" (which is presumably the study of pens) simply demonstrates a lack of understanding of what Computer Science is.
The point of the analogy is that implementation -- essentially what CS is all about -- is not interesting just as the way you construct a pen or use it to write grammatical sentences is not interesting.
Computer Science is not about how to build a computer.
Computer Science is about what you can do with a computer. Google's pagerank is computer science. Recommendation systems, like Amazon and Netflix use, are computer science. Computer science is about discovering new ways to design bridges -- not about building them.
Implementation here refers to software as well.
Computer Science is about what you can do with a computer.
Not really. The vast majority of CS research papers are not about new uses of a computer.
Let me guess: you're not a big fan of Knuth either?
But clearly, we need to go beyond this and think about apps too.
But you can still have the case that the web 2.0 apps are much more interesting than the CS concepts on which they are based.
Which is more interesting, opera or football? Personally, I'm interested in opera -- and Computer Science -- but I'm willing to accept that most people find football (and web 2.0 applications) to be far more interesting.
But you thinking that Computer Science is boring doesn't imply that Computer Science is analogous to studying pens any more than me thinking that football is boring implies that football is analogous to the mating behaviour of male elk. In both cases there is similarity at first glance -- Computer Science courses tend to focus on very simple and well-understood algorithms (quicksort, binary search, minimal spanning tree, etc.), while to someone without understanding of tactics, football appears to be nothing more than a bunch of large males running at and into each other -- but if you take the time to understand either of these you'll see that the analogies fail quite quickly.
By which you mean, one makes the other possible?
In the middle ages, can you imagine the trouble it was to make your own ink, collect and maintain quills of the appropriate type, train oneself to wield the quill skillfully and not cause inkblots, and finally deal with the fatigue of manipulating such a large object?
Nowadays pens are so cheap and easy to use you never even have to think about it. So you move onto other questions, like what to write.
Response #2:
This statement is idiotic. Computer science is essential to the collection of technologies people call "Web 2.0".
The most advanced Web 2.0 sites allow for quick search across enormous databases, and efficient, many-to-many messaging. These problems are hard. Using the appropriate algorithm is essential to scalability. Look at Facebook; they deploy Stanford whiz kids to invent their own infrastructure (hmmm, that sounds familiar) and they're growing faster than anybody else in this space.
Ok, to tell you the truth -- this is something I've wondered about recently myself. I happen to know about the codebases of several successful Web 2.0 sites post-acquisition. And in many cases, they used the naive solution and got away with it until acquisition. It's difficult to blog about these things in public, but I've circulated similar speculations privately, that maybe all CS knowledge is a huge waste of time for entrepreneurs.
Using naive solutions has definitely worked for some startups. But it comes at a fairly heavy price. You are essentially betting everything on being acquired before you get so slow that your own users start hating you. Once acquired, you then get a reprieve from death, and then you spend about one year building your 2.0 version that actually scales decently (all the while fighting fires with the clunky 1.0 version). Meanwhile your users scratch their heads wondering why, once you got all that money, you stopped building any new features. This pattern has been repeated many times for successful web 2.0 startups.
Contrast that situation with a company like Google or Facebook. One of Google's main advantages was scaling, from their algorithms to their ability to create vast computing infrastructures. Facebook acquired this sort of talent a little bit later in their history, but they are definitely there today. So when they got offers to buy their company for millions of dollars -- even a billion dollars -- they were able to say no. Because they knew they could grow faster by themselves. Last year Zuckerberg was considered an idiot for turning down a billion dollars. But he knew that F8 was in the pipeline, and he was very smart to say no.
Being able to scale means freedom. Ignoring scalability is a high-stakes bet. But either strategy might work, depending on what the startup's business model is, and the talents and inclinations of the founders.
The basic work on relational databases was done by computer science researchers. And actually people in labs built the Internet, come to think of it. And they pioneered the ideas behind dynamic languages like Ruby. Before there was Matz or Larry there was Alan Kay and Guy Steele.
What would we do without computer science researchers?