Easily, just the way Facebook does it except maybe better, with one consideration -- they will have to work their way into such work. Let's see: For such scal

Easily, just the way Facebook does it except maybe better, with one consideration -- they will have to work their way into such work. Let's see: For such scaling, it has long been the case that a first-cut quantitative approach has been theoretical and empirical network queuing analysis. So, how many such Facebook scaling architects are able to do such analysis, either theoretically or empirically? I'll bet, not many. Net, I doubt that the Facebook scaling architects have a very good approach to the problem. What are they doing? They have a good grasp of the basic issues of the components, that is, the server hard/software, NICs, LAN switches, TCP/IP stack details, Linux thread switching performance, etc. Then they concentrate on the bottlenecks, solve those empirically one at a time, and otherwise just f'get about the rest. Right? I mean, what the heck else are they going to do, dig into the Poisson process hypotheses and the renewal theorem? I doubt it. So, sure, a humanities major won't come knowing all about the time/date stamps on Linux files or about file locking. That may be stuff they have to learn. So, for more, need people who can learn stuff, find materials for the learning, work with people for the learning, use some critical thinking about the material and how to use it. Then for implementing the results of the analysis, have to involve other people, in software, hardware, cable pulling, HVAC, electrical power, ..., lots of other people. So, now have to work with people -- with technical papers, planning documents, foil decks, presentations, meetings small to large, one on one discussions, etc. So, have work with egos, power struggles, turf battles, office romances, human nature, etc., i.e., the stuff nerds ignored (I'm an expert nerd) in high school, college, and beyond. The Heine-Borel theorem, fine; human nature, f'get about it. So, after I saw Branson's remark, I happened to visit the Web site of my college and, there, saw some of the undergraduate students they were proud of. I doubt that any of those students knew anything about Linux internals, but one of the students in just her extracurricular activities has organized nearly everything on campus short of the birds in the trees. Give her a couple of years, starting as I outlined, yes with her able to learn about time stamps on files, etc., and when it's time to scale the Web site, along with moving it to a colo or our own building, I'd bet she'd knock the socks off nearly all nerds, including me. And, if really need some good work, say, in queuing, bet she'd blow away the self-taught Linux hackers who started with C++ in middle school; for one, she'd be smart enough and good enough to pick a good consultant in, say, computer and network performance at a computer science department and make good use of some consulting. Again, I bet that so far the Linux performance details remain nearly all fairly simple conceptually. Yes, good thread switching likely remains a challenge, but that's quite specialized work for which draw the larger lessons from specialists. I'll provide an example: I was working in artificial intelligence (AI). We developed an AI language and did joint work with MET LIFE and GM and gave a paper at an AAAI IAAI conference at Stanford. My wife wanted to learn some of this material. So I gave her a lecture of about 15 minutes on how to connect to the server and use it and then another 15 minutes on our AI language. She then took two weeks and wrote a nice, first AI program. Right: BAM, with next to no background in programming. I looked at her program and said, "It's a program. It works. It does what you wanted. There's nothing fundamentally wrong with it. But 'AI' has a 'belief', a 'theme', maybe just a 'hope', and you didn't really illustrate that ...." So, building on some of what she'd studied as an undergraduate, I explained the 'dreams' of the MIT 'school' of AI. She smiled. Two weeks later she had a really nice first AI program. "Nice"? Our project had as programmers some of the brightest computer science students in the country, who were taking computing and AI very seriously, and they had written first, sample programs. Her program was several notches better, the best first AI program our group ever saw. She did that work with all of about 45 minutes of instruction from me and four weeks of time. Of course, she was 'cheating': She was brilliant, not just a little but the real thing. Yes, high school Valedictorian and in college PBK, 'Summa Cum Laude', Woodrow Wilson, NSF, etc. She got her Ph.D. in essentially mathematical sociology from one of the world's best research universities and where two of her professors became President of the American Sociological Association. Did I mention she was brilliant? This detailed computer stuff can be picked up, fairly quickly, especially if it is well presented. Good students can be darned good at picking up such stuff, including from some horribly badly written documentation, e.g., as in the computer industry. I'm guessing that maybe Branson had a point. That is, it may be better to get good smarts, ability to learn, especially from poorly organized materials, really good at the '3Rs', and really good working with groups of people and just pick up over, say, two years, what need to know about a growing server farm based on Windows Server and SQL Server and my software (a particular, just one, growing server farm, not all possible growing server farms) instead of hiring for Windows Server, etc. right away. Maybe. I'm not fixed in my view but wondering. Where am I right/wrong?