I rest my case :
Author: Edouard Chazal
Why People Pay To Read The New York Times
In the United States, the ranks of journalists keep shrinking. As I travel around the world for The New York Times, I hear from journalists everywhere about the painful downsizing happening across the industry. This has meant important stories go untold. Costly investigative reporting units pare back their ambition in the face of budget cuts. Expensive trips to conflict zones suddenly seem like a luxury publishers cannot afford, and news organizations everywhere rely more and more on wire services to cover the world. This has reduced the vibrancy and diversity of the journalism we consume, and the world is poorer for it. Above all, local journalism has suffered. Cities that once supported two or more daily newspapers find themselves with one, or none at all.
Learning to Love Complex Numbers
Numbers are curious things. On one hand, they represent one of the most natural things known to humans, which is quantity. It’s so natural to humans that even newborn babies are in tune with the difference between quantities of objects between 1 and 3, in that they notice when quantity changes much more vividly than other features like color or shape.
But our familiarity with quantity doesn’t change the fact that numbers themselves (as an idea) are a human invention. And they’re not like most human inventions, the kinds where you have to tinker with gears or circuits to get a machine that makes your cappuccino. No, these are mathematical inventions. These inventions exist only in our minds.
A Magical Answer to an 80-Year-Old Puzzle
A simplified version of the problem goes like this: Imagine that you are imprisoned in a tunnel that opens out onto a precipice two paces to your left, and a pit of vipers two paces to your right. To torment you, your evil captor forces you to take a series of steps to the left and right. You need to devise a series that will allow you to avoid the hazards — if you take a step to the right, for example, you’ll want your second step to be to the left, to avoid falling off the cliff. You might try alternating right and left steps, but here’s the catch: You have to list your planned steps ahead of time, and your captor might have you take every second step on your list (starting at the second step), or every third step (starting at the third), or some other skip-counting sequence. Is there a list of steps that will keep you alive, no matter what sequence your captor chooses?
Big Data’s Mathematical Mysteries
At a dinner I attended some years ago, the distinguished differential geometer Eugenio Calabi volunteered to me his tongue-in-cheek distinction between pure and applied mathematicians. A pure mathematician, when stuck on the problem under study, often decides to narrow the problem further and so avoid the obstruction. An applied mathematician interprets being stuck as an indication that it is time to learn more mathematics and find better tools.
I have always loved this point of view; it explains how applied mathematicians will always need to make use of the new concepts and structures that are constantly being developed in more foundational mathematics. This is particularly evident today in the ongoing effort to understand “big data” — data sets that are too large or complex to be understood using traditional data-processing techniques.
Our current mathematical understanding of many techniques that are central to the ongoing big-data revolution is inadequate, at best. Consider the simplest case, that of supervised learning, which has been used by companies such as Google, Facebook and Apple to create voice- or image-recognition technologies with a near-human level of accuracy. These systems start with a massive corpus of training samples — millions or billions of images or voice recordings — which are used to train a deep neural network to spot statistical regularities. As in other areas of machine learning, the hope is that computers can churn through enough data to “learn” the task: Instead of being programmed with the detailed steps necessary for the decision process, the computers follow algorithms that gradually lead them to focus on the relevant patterns.
Abnormal Capitalist 