Every new technology begins with naive euphoria — its inventor(s) are usually submersed in the ideas themselves; it is their immediate colleagues that experience most of the wild enthusiasm. Most technologies are overpromised, more often than not simply to generate funds to continue the work, for funding is an integral part of scientific development; without it, only the most imaginative and revolutionary ideas make it beyond the embryonic stage. Hype is a natural handmaiden to overpromise, and most technologies build rapidly to a peak of hype. Following this, there is almost always an overreaction to ideas that are not fully developed, and this inevitably leads to a crash of sorts, followed by a period of wallowing in the depths of cynicism. Many new technologies evolve to this point, and then fade away. The ones that survive do so because someone finds a good use (= true user benefit) for the basic ideas.

Schmidt’s thesis is simple and bold: it was the urge to worship that brought mankind together in the very first urban conglomerations. The need to build and maintain this temple, he says, drove the builders to seek stable food sources, like grains and animals that could be domesticated, and then to settle down to guard their new way of life. The temple begat the city.

There are more than 4000 airports served by commercial airlines worldwide. Averaged uniformly, each airport has an outgoing degree of 8 (it has flights to 8 other airports), and is served by 4 airlines. However large airports dominate the system: re-weighted by their number of departures, airports average degree 64. This reflects the hub-and-spoke system used by many airlines, wherein for a given airline one to four airports account for half of their departures. Despite the high connectivity amongst the major airports, the shortest path between two airports chosen uniformly averages 3.5 flights in the United States and 5 worldwide. Amazingly, the graph diameter is often as high as 20: there are airports that can take 20 flights minimum to get between, over 4 days (typically this will be a small airport in Alaska or Canada to another small airport in Africa or Indonesia).

After just a single month, a full 25% of the URLs are what we call “unverifiable”. By that I mean that the content was either duplicate, included session parameters, or for some reason could not be retrieved (verified) again (404s, 500s, etc.). Six months later, 75% of the tens of billions of URLs we’ve seen are “unverifiable” and a year later, only 20% qualifies for “verified” status. As Rand noted earlier this week, Google’s doing a lot of verifying themselves.

While supervised algorithms aim to minimize the classification error, unsupervised algorithms aim to create groups or subsets of the data where data points belonging to a cluster are as similar to each other as possible, while making the difference between the clusters as high as possible.

On the other hand, there is some good news about being big—it makes it feasible to maintain a constant body temperature. This has several advantages. For example, it is easier to evolve efficient muscles if they are only required to function in a narrow range of temperatures than if they must perform well over a wide range of temperatures. However, this temperature control comes at a price. Warm blooded creatures (unlike insects) must devote a substantial part of their food energy simply to keeping warm. For an adult human, this is a pound or two of food per day. For a mouse, which has about one-twentieth the dimensions of a human, and hence twenty times the surface area per unit volume, the required food for maintaining the same body temperature is twenty times as much as a fraction of body weight, and a mouse must consume a quarter of its own body weight daily just to stay warm. This is why, in the arctic land of Spitzbergen, the smallest mammal is the fox.

This is the exact analogue of an open source software failure mode: often companies think they can get all the benefits of open source simply by releasing their source code. The best dinner parties are about the other people. Similarly, the best open source projects have great people, attract great people, and the source is simply what they’re working on: necessary but not sufficient. You can build it but they won’t come. All successful open source projects build communities of supportive engaged developers who identify with the project and keep it productive and useful.

Here’s the problem: in my experience, if you know what you’re doing, the odds of a given executive hire working out will be about 50/50. That is, about 50% of the time you’ll screw up and ultimately have to replace the person. (If you don’t know what you’re doing, your failure rate will be closer to 100%.) Why? People are people. People are complicated. People have flaws. You often don’t know what those flaws are until after you get to know them. Those flaws are often fatal in an executive role. And more generally, sometimes the fit just isn’t there.

Those who initially scored high for “grit”—defined as perseverance and a passion for long-term goals, and measured using a short multiple-choice test—were 31 percent more likely than their less gritty peers to spur academic growth in their students. Gritty people, the theory goes, work harder and stay committed to their goals longer. (Grit also predicts retention of cadets at West Point, Duckworth has found.)

This tale of two boys, and of the millions of kids just like them, embodies the most stunning finding to come out of education research in the past decade: more than any other variable in education—more than schools or curriculum—teachers matter. Put concretely, if Mr. Taylor’s student continued to learn at the same level for a few more years, his test scores would be no different from those of his more affluent peers in Northwest D.C. And if these two boys were to keep their respective teachers for three years, their lives would likely diverge forever. By high school, the compounded effects of the strong teacher—or the weak one—would become too great.

But ignorance allows you to “…force yourself to be smart. You use what you know in terms of company building, supporting entrepreneurs, discovering the market. We will design the product around what the market needs with an intuition, but then we’ll go and test it. We don’t want to be smarter than the market we are entering.