This seems like a great time to post the phenomenal Everything is a Remix [1]. Part one discusses movies, part two film, and part three discusses interfaces for computers, with special emphasis on Xerox PARC, Apple, and the Mac.
You could enhance that second point by adding some noise to the function so the difficulty isn't a smooth ramp — you get some tough monsters earlier and then maybe the next group isn't as difficult.
Definitely after. Cooking denatures the myosin and releases water; a seared steak soaking in water isn't going to have the kind of texture you'll get (and want!) from the Maillard reaction.
I guess what I mean is that it'll taste fine but the texture won't be quite there.
The worst part of R is that array indices begin at 1, and trying to get an array at 0 will fail silently by returning 0. I've spent many a night trying to figure out why all my data is wrong because my_array[0] * frame$column is returning the wrong numbers.
Not everyone measures success by money and leisure time. Especially in more creatively-derived industries, like culinary arts, I find that money has little to do with what people judge as success. Many simply want to make the best food they can.
The fact that he's just using canny suggests to me that it's just a simple hack he threw together. There are LOTS of other edge detection algorithms, but canny is pretty good and so easy to implement that it's the most generally used. It's not great at faces at a low resolution, but even just a little pre-processing can make the image better (as he demonstrates towards the bottom of the page).
What I meant was to shy away from approaches that are PURELY based on statistics if you have no background in it, because it can get overwhelming quickly.
Of course, if it's worth it to invest the time required to have a fundamental understanding of statistics, by all means do so -- but if this is a one-time or a short-term project, I'm not sure the time commitment is worth it.
Edward Tufte's book The Visual Display of Quantitative Information is a monumental book. He writes not about how to make your graphs look pretty, but how to display vast quantities of data and distill them down into useful graphics that communicate themselves effectively.
He provides examples of good and bad graphs, but more importantly, explains what exactly it is that makes those examples good and bad, and further generalizes it so you understand how to make good visualizations. If you don't want to shell out the money for it, it's probably at your library (remember those?).
Additionally, if I were you, I'd stay way from statistical approaches to displaying information unless you have some background or are willing to learn about it -- it tends to be highly technical and is probably too complex for what you're trying to do. Basic stats might help you, but not as much as Tufte will.
If the iPhone was going to threaten Nintendo, it would have done it already. Game Center-like backends are hardly uncommon on it. OpenFeint has been around for a long time, and it's pretty prevalent.
This gives me that really excited feeling in my gut that I get when I see something cool. I've always wanted to learn how to play piano, but I was always overwhelmed by diving right in. This is why the iPad is going to be so cool.
Do you have plans to do this for other instruments? I can see it being enormously popular for guitar tab, especially if you can add your own tabs to it.
EDIT: Additionally, I think $3 is a perfect introductory price. If you've built a large enough following, you can leverage that to increase the price (perhaps by offering updates/large additional music libraries?) at a later date.
So what you're REALLY providing isn't a quote-aggregation service, but rather an intelligent method of showing people content from around the internet based on how much they like a topic.