The recordings that burned up in the Universal fire — like the songs that are blasting from car windows on the street outside your home, like all the records that you or I or anyone else has ever heard — represent a wonderment that we have come to take for granted. For most of human history, every word spoken, every song sung, was by definition ephemeral: Air vibrated and sound traveled in and out of earshot, never to be heard again. But technology gave humanity the means to catch sounds, to transform a soprano’s warble, a violin’s trill, Chuck Berry’s blaring guitar, into something permanent and repeatable, a sonic artifact to which listeners can return again and again.
The new Jesko by Koenigsegg, named after the company founder’s father, is claimed to be the world’s first road-legal 300 mph car. That top speed translates to more than 480 kilometers per hour. To put it in more relatable terms, this car can travel fast enough to cover the length of a football field — doesn’t matter which version of football you prefer — in less than a second. When you think of it in those terms, you’ll probably also realize just how theoretical performance like that is: there aren’t many straight lines in the world long enough to let a person hit such ludicrous speeds.
Nostalgia, to me, is not the emotion that follows a longing for something you lost, or for something you never had to begin with, or that never really existed at all. It’s not even, not really, the feeling that arises when you realize that you missed out on a chance to see something, to know someone, to be a part of some adventure or enterprise or milieu that will never come again. Nostalgia, most truly and most meaningfully, is the emotional experience—always momentary, always fragile—of having what you lost or never had, of seeing what you missed seeing, of meeting the people you missed knowing, of sipping coffee in the storied cafés that are now hot-yoga studios. It’s the feeling that overcomes you when some minor vanished beauty of the world is momentarily restored, whether summoned by art or by the accidental enchantment of a painted advertisement for Sen-Sen, say, or Bromo-Seltzer, hidden for decades, then suddenly revealed on a brick wall when a neighboring building is torn down. In that moment, you are connected; you have placed a phone call directly into the past and heard an answering voice.
Illustration : Eleni Kalorkoti
That night, as darkness enveloped the family’s three-story mud-brick compound, Wasil’s uncles shuffled Hamidullah’s bloodied corpse inside. The boy drew close, his cheeks wet with tears. In the low light, he could see the blood that stained his father’s clothes. He was a child, yes, but he knew enough of his world to realize, without even asking, who had killed his father. And he knew what it meant for him.
In the weeks that followed, Wasil’s anger hardened into a grim and brutal ambition—one that would launch him toward fame and then toward tragedy. “Teach me how to shoot,” Wasil said to his uncle Samad when he had resolved himself to retribution. “I want to kill my father’s killer.”
Yitang “Tom” Zhang spent the seven years following the completion of his Ph.D. in mathematics floating between Kentucky and Queens, working for a chain of Subway restaurants, and doing odd accounting work. Now he is on a lecture tour that includes stops at Harvard, Columbia, Caltech, and Princeton, is fielding multiple professorship offers, and spends two hours a day dealing with the press. That’s because, in April, Zhang proved a theorem that had eluded mathematicians for a century or more. When we called Zhang to see what he thought of being thrust into the spotlight, we found a shy, modest man, genuinely disinterested in all the fuss.
Q : Did you experience any emotions when you realized you’d solved the problem?
A : Not so much. I am a very quiet person.
Q : Were you excited?
A : A little. Not too much.
Edit : Here’s a link to a documentary on Yitang : Counting From Infinity.
This didn’t just threaten Oesterlund’s fortune. It also had the potential to carve open a portal into the world of offshore finance, a place that the global elite has spent hundreds of millions of dollars to build and defend. In the offshore archipelago, their interests are hidden behind shell companies and trusts, their anonymity guaranteed under the law, from Delaware to the Bahamas to the South Pacific. James S. Henry, a former chief economist at McKinsey, calls the offshore financial world the “economic equivalent of an astrophysical black hole,” holding at least $21 trillion of the world’s financial wealth, more than the gross domestic product of the United States.
And yet the rise of machine learning makes it more difficult for us to carve out a special place for us. If you believe, with Searle, that there is something special about human “insight,” you can draw a clear line that separates the human from the automated. If you agree with Searle’s antagonists, you can’t. It is understandable why so many people cling fast to the former view. At a 2015 M.I.T. conference about the roots of artificial intelligence, Noam Chomsky was asked what he thought of machine learning. He pooh-poohed the whole enterprise as mere statistical prediction, a glorified weather forecast. Even if neural translation attained perfect functionality, it would reveal nothing profound about the underlying nature of language. It could never tell you if a pronoun took the dative or the accusative case. This kind of prediction makes for a good tool to accomplish our ends, but it doesn’t succeed by the standards of furthering our understanding of why things happen the way they do. A machine can already detect tumors in medical scans better than human radiologists, but the machine can’t tell you what’s causing the cancer.