Michael Wolff:

Facebook is not only on course to go bust, but will take the rest of the ad-supported Web with it.<p>

Given its vast cash reserves and the glacial pace of business reckonings, that will sound hyperbolic. But that doesn't mean it isn't true.

A dramatic exposition of what happens when growing inventory (space to put ads in) meets limited advertising numbers. Extreme, but none of it seems impossible.

Facebook is not only on course to go bust, but will take the rest of the ad-supported Web with it. Given its vast cash reserves and the glacial pace of business reckonings, that will sound hyperbolic. But that doesn't mean it isn't true.

"When faced with the task of forecasting a dynamic system, practitioners often have available historical data, knowledge of the system, or a combination of both. While intuition dictates that perfect knowledge of the system should in theory yield perfect forecasting, often knowledge of the system is only partially known, known up to parameters, or known incorrectly. In contrast, forecasting using previous data without any process knowledge might result in accurate prediction for simple systems, but will fail for highly nonlinear and chaotic systems. In this paper, the authors demonstrate how even in chaotic systems, forecasting with historical data is preferable to using process knowledge if this knowledge exhibits certain forms of misspecification. Through an extensive simulation study, a range of misspecification and forecasting scenarios are examined with the goal of gaining an improved understanding of the circumstances under which forecasting from historical data is to be preferred over using process knowledge."

Closer to the truth

Good points but misses the significance of data

"On one occasion he decided he did not want to eat a particular vegetable for dinner. We said that he wouldn’t be leaving the table until he did so. I said, 'now use your game theory to forecast what the outcome of this is and let me know what you decide.' He laid out his options, our reactions and everyone’s payoffs and worked out that he would do well to eat his vegetables sooner rather than later."

"Recent theory work has found that a special type of spatial partition tree - called a random projection tree - is adaptive to the intrinsic dimension of the data from which it is built. Here we examine this same question, with a combination of theory and experiments, for a broader class of trees that includes k-d trees, dyadic trees, and PCA trees. Our motivation is to get a feel for (i) the kind of intrinsic low dimensional structure that can be empirically verified, (ii) the extent to which a spatial partition can exploit such structure, and (iii) the implications for standard statistical tasks such as regression, vector quantization, and nearest neighbor search."

Interesting analysis about parties in power and deficit spending

kalman filter to make things nice & tidy. awesome