Or people that develop for smartphones. Or people that develop on embedded systems/consumer electronics. Or people that work with raw bitmaps (eg games writers).

You need to get out more if you think (as your comment would seem to suggest) that only Google has efficiency problems...

Wait, so instead of spending a semester learning about algorithms and stuff, I can go throw money at the problem?

Why am I in school?

Didn't you guys just pass 20,000 employees?

You may not have intended it, but your comment reads as "Google has awesome hard problems that only badasses can work on" "Also, I work there". Not ever mention of one's workplace warrants a disclaimer. :)

But you do bring up an interesting point, how does Google handle the heterogeneous server problem? One assumes that not all nodes are created equal (if only because it would be cost prohibitive to upgrade all at once), so do you just use dynamic task scheduling and hope for the best or is there something cooler going on there?

If you have only one server, then you are going to add $xx; instead of spending $xxxx fixing it.

Google has to add $xx * the number of its' servers vs. $xxxx fixing it by one or two developers.

Few people work for Google or tackle problems that size. Buying more RAM is most of the time a quick and economical solution.

I think that's more of a disclosure than a disclaimer.