A similar application was to use aerogels, which are highly insulating but not reflective, as clothing insulation. I recall a number of companies have explored this in the past [1]. The issue with aeogels appears to be two-fold: firstly, they are relatively expensive to manufacture, but secondly, the resulting garments are often too warm!
The arrest rate is also different from the incarceration rate, which is much more heavily skewed. According to Pew, black men are incarcerated at ~6.5 the rate that white men are, per capita[1].
This seems quite similar to the design AOL's Alto [1] used. I actually used Alto for a while, but found that the promotional images were less helpful than the short blurbs Gmail had already for quickly figuring out if I wanted to open a message, even one promotional in nature.
This is actually one of the tuition options that the US armed forces offers students: we pay for your schooling, and you serve in the military for an equal number of years. It's also quite common for your company to pay for business school for a promising employee as well.
In ROTC programs, you also get military training while in school. They just don't pay for your tuition, it's an entire program, done with other recruits.
For anyone looking, there are also a number of sites dedicated to just this, with a similar audience to HN. Betalist[1], Cloudlist[2], and ErliBird[3] are examples that come to mind which I've had good experiences with.
I think a major hurdle we have to overcome with big data is separating causation vs correlation. As the data set scales, we gain ever-increasing confidence in the correlation, but an ever more complex set of causations.
Take their House of Cards example. Netflix saw a strong correlation between David Fincher, Political Thrillers, and Kevin Spacey. Fantastic. But why? What did people like about these things? Why did this 'work'?
Let's try to replicate this decision: take great directors (Wachowski siblings), a strong cast (Emille Hirsch, John Goodman, Susan Sarandon), and nearly unlimited budget ($200m) to reboot an existing, well received franchise. Should be a hit, right? Wrong - it's a complete and utter failure known as 2008's Speed Racer.
When we say we want to be data-driven we actually mean we want to be insights-driven. We want to understanding the "Why?" from the data's "What"; it's the 'Why' which lets us know how to react next. It's easy to confuse the data's specificity with insight's certainty, but they are distinctly not the same: We can pinpoint conversions down to 6 digits of significance without having a clue why it occurs.
What we really need is Big Insight, but that's a significantly harder problem, not because we don't have the technology to create a solution, but because don't even know what the right questions are.
I'm optimistic about the possibilities of a system like IBM's Watson in helping solve this, but as it stands, Big Data's utility is giving us 99.755% certainty that we have no idea what is going on.
This is a masterpiece of a backhanded compliment. Never have I seen such elegant transitions between briefly masked contempt and half-hearted admiration. It's really stunning.
I think analyzing these acquisitions from a raw dollars-to-dollars perspective is a mistake. When doing a turnaround with a company so fundamentally troubled as Yahoo, you need more than just a few patch-in acquisitions, so that's clearly not what they are about. These moves are part of a long term investment in motivating employees, building relationships with the valley, and regaining footing in the markets that they can win.
Yeah, I'm having trouble seeing the advantage of this over the browser's native implementation: Chrome's CMD+SHIFT+I hotkey brings up a mail this page window automatically for me.
I would definitely put some effort into copywriting the main benefits into that landing page.
People forget about the amount of data LinkedIn has available to them: ConnectedHQ (the predecessor to LinkedIn Contacts) has direct access to thousands of email inboxes, Rapportive can log any time someone hovers over a new address, and millions of connections have been gleaned through 'import your contacts'.
If you really want to talk about creepy, I'm fairly sure they use your IP address to match against other people who live/work at the same location: when I created a test account with dummy information, the first contacts that were suggested to me were my roommates.
I've been thinking about this as well; the results I could find are from quite a while ago, but in general the answer is to use a reversible encryption like AES [1] along with secure storage of the encryption key [2], preferably on another server or in an isolated part of the server. Not particularly satisfying, is it...
[1] http://www.outsideonline.com/outdoor-gear/clothing-apparel/H...