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.
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.
On making friends with animals—the story of my life :
There was a canopy of leaves over my head. Once I moved beyond it, the moon lit my path, so I turned off the flashlight. I’d expected Carol to be gone by that point, but for the next half mile, all the way home, she walked with me, sometimes by my side and sometimes a few steps ahead, leading the way. No cars approached or passed. The road was ours, and we marched right down the center of it, all the way to the front of the house and then through the garden gate to the kitchen door. Just me and my wild friend Carol.