Not to hijack this post, but I'm saddened every time I see anything monte carlo related referred to as the metropolis algorithm. When you're the boss, what you say goes.
For those of you that don't know about Slackware. Slackware is the oldest distro and it is still plenty alive today. When to setup linux on my computer in the early days with other distros (red hat/suse/etc), this would eventually crap up (rpm hell) and give me something unusable. Using Slackware forces you understand how everything works in a linux distro. This lets you fix your own problems.
Low growth causes more income to come from capital, which causes more inequality due to inheritance and the rich getting richer. The solution is a global progressive tax on capital.
There's a paper in the Clinical Chemistry and Laboratory Medicine journal titled, "Theranos phenomenon: promises and fallacies" [1]. It says most of the cost are related to overhead and personnel, not technology. Consumables are cheap. Also it is entirely possible that tests are being subsidized with VC money currently. I don't know what they would have to charge to be cash flow positive.
You can also run Alexa from your desktop and integrate Alexa to any other physical device besides the Echo with the Alexa Voice Service. Great for those who want to play with Alexa, but don't want to shell out money for an Echo. Amazon has an easy to follow reference implementation for this. https://developer.amazon.com/public/solutions/alexa/alexa-vo...
Fancy socks is a silicon valley thing according to this New York Times article since people normally dress down. If everyone is wearing t-shirt and jeans, socks become your differentiator.
http://www.nytimes.com/2012/02/05/fashion/in-silicon-valley-...
I've been trying to read one book a week since 2013 (http://warrenmar.wordpress.com/book-of-the-week/). I think everyone should try it. I never read that much when I was in school, but now I really enjoy it.
This principle is used in aquaponics in the form of a bell siphon. You don't want to keep the roots of your plans submerged for long periods of time, so this lets you flush out the water automatically.
"weaker" metrics can be useful, because you can understand it better. If I tell you a PageRank of an author is 3.452. That means nothing to me. If I tell you somebody's h-index is 18. That means they published 18 papers that got 18 citations each. The h-index is useful for comparing people in the same field. There is also a metric for journals called impact factor.
The original funding Larry got was from the Digital Library Initiative. Then the web blew up. Maybe I shouldn't say PageRank was designed for citations, but that is where it draws its influence from. Things don't magically pop out of no where. But if you look at the PageRank algorithm, it looks like it is designed for paper citations. As a graduate student, you start a some place and you end up at a different place from where you intended to end up.
My point is that one shouldn't be surprised to see that PageRank would work well for paper citations.
Amazon hosts public datasets at
https://aws.amazon.com/publicdatasets/
Good if you want to quickly spin up an instance, copy data over from s3 and process it.