Brian Christian Quotes
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In one particularly dramatic case, an officer instinctively grabbed the gun out of the hands of an assailant and then instinctively handed it right back—just as he had done time and time again with his trainers in practice.
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This approach, called Simulated Annealing, seemed like an intriguing way to map physics onto problem solving. But would it work? The initial reaction among more traditional optimization researchers was that this whole approach just seemed a little too … metaphorical. “I couldn’t convince math people that this messy stuff with temperatures, all this analogy-based stuff, was real,” says Kirkpatrick, “because mathematicians are trained to really distrust intuition.
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We say brain fart when we should really say cache miss.
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And here, the children who had learned that the experimenter was unreliable were more likely to eat the marshmallow before she came back, losing the opportunity to earn a second treat. Failing the marshmallow test—and being less successful in later life—may not be about lacking willpower. It could be a result of believing that adults are not dependable: that they can’t be trusted to keep their word, that they disappear for intervals of arbitrary length. Learning self-control is important, but it’s equally important to grow up in an environment where adults are consistently present and trustworthy.
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When then senator Obama visited Google in 2007, CEO Eric Schmidt jokingly began the Q&A like a job interview, asking him, “What’s the best way to sort a million thirty-two-bit integers?” Without missing a beat, Obama cracked a wry smile and replied, “I think the Bubble Sort would be the wrong way to go.” The crowd of Google engineers erupted in cheers. “He had me at Bubble Sort,” one later recalled.
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One of the implicit principles of computer science, as odd as it may sound, is that computation is bad: the underlying directive of any good algorithm is to minimize the labor of thought.
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Living by the wisdom of computer science doesn’t sound so bad after all. And unlike most advice, it’s backed up by proofs.
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Inspired by the punched railway tickets of the time, an inventor by the name of Herman Hollerith devised a system of punched manila cards to store information, and a machine, which he called the Hollerith Machine, to count and sort them. Hollerith was awarded a patent in 1889, and the government adopted the Hollerith Machine for the 1890 census. No one had ever seen anything like it. Wrote one awestruck observer, “The apparatus works as unerringly as the mills of the Gods, but beats them hollow as to speed.” Another, however, reasoned that the invention was of limited use: “As no one will ever use it but governments, the inventor will not likely get very rich.” This prediction, which Hollerith clipped and saved, would not prove entirely correct. Hollerith’s firm merged with several others in 1911 to become the Computing-Tabulating-Recording Company. A few years later it was renamed—to International Business Machines, or IBM.
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The intuitive standard for rational decision making is carefully considering all available options and taking the best one. At first glance, computers look like the paragons of this approach, grinding their way through complex computations for as long as it takes to get perfect answers. But as we've seen, that is an outdated picture of what computers do; it's a luxury afforded by an easy problem. In the hard cases, the best algorithms are all about doing what makes the most sense in the least amount of time, which by no means giving careful consideration to every factor and pursuing every computation to the end. Life is just too complicated for that.
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Consider how many times you’ve seen either a crashed plane or a crashed car. It’s entirely possible you’ve seen roughly as many of each—yet many of those cars were on the road next to you, whereas the planes were probably on another continent, transmitted to you via the Internet or television. In the United States, for instance, the total number of people who have lost their lives in commercial plane crashes since the year 2000 would not be enough to fill Carnegie Hall even half full. In contrast, the number of people in the United States killed in car accidents over that same time is greater than the entire population of Wyoming.
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As the saying goes, the most exciting phrase to hear in science, the one that heralds new discoveries, is not ‘Eureka!’ but ‘That’s funny.
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Minimizing the sum of completion times leads to a very simple optimal algorithm called Shortest Processing Time: always do the quickest task you can.
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We asked Shoup if his research allows him to optimize his own commute, through the Los Angeles traffic to his office at UCLA. Does arguably the world’s top expert on parking have some kind of secret weapon? He does: “I ride my bike.
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If meaning lies even partially in usage, then you subtly alter the language every time you use it. You couldn't leave it intact if you tried
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They would randomly assign patients to either ECMO or the conventional treatment until a prespecified number of deaths was observed in one of the groups. Then they would switch all the patients in the study to the more effective treatment of the two.
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Searcher, there is no road. We make the road by walking.
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Look-Then-Leap Rule: You set a predetermined amount of time for “looking”—that is, exploring your options, gathering data—in which you categorically don’t choose anyone, no matter how impressive. After that point, you enter the “leap” phase, prepared to instantly commit to anyone who outshines the best applicant you saw in the look phase.
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It’s amazing,” he says, “how someone’s IQ seems to double as soon as you give them responsibility and indicate that you trust them.” And, as far too many can attest, how it halves when you take that responsibility and trust away.
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Seemingly innocuous language like 'Oh, I'm flexible' or 'What do you want to do tonight?' has a dark computational underbelly that should make you think twice. It has the veneer of kindness about it, but it does two deeply alarming things. First, it passes the cognitive buck: 'Here's a problem, you handle it.' Second, by not stating your preferences, it invites the others to simulate or imagine them. And as we have seen, the simulation of the minds of others is one of the biggest computational challenges a mind or machine can ever face.
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Cobbled-together bits of human interaction do not a human relationship make. Not fifty one-night stands, not fifty speed dates, not fifty transfers through the bureaucratic pachinko. No more than sapling tied to sapling, oak though they may be, makes an oak.
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To be human is to be a human, a specific person with a life history and idiosyncrasy and point of view; artificial intelligence suggest that the line between intelligent machines and people blurs most when a puree is made of that identity.
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Grandmaster games are said to begin with novelty, which is the first move of the game that exits the book. It could be the fifth, it could be the thirty-fifth. We think about a chess game as beginning with move one and ending with checkmate. But this is not the case. The games begins when it gets out of book, and it end when it goes into book..And this is why Game 6 [between Garry Kasparov and Deep Blue] didn't count...Tripping and falling into a well on your way to the field of battle is not the same thing as dying in it...Deep Blue is only itself out of book; prior to that it is nothing. Just the ghosts of the game itself.
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There are many ways to relax a problem, and we’ve seen three of the most important. The first, Constraint Relaxation, simply removes some constraints altogether and makes progress on a looser form of the problem before coming back to reality. The second, Continuous Relaxation, turns discrete or binary choices into continua: when deciding between iced tea and lemonade, first imagine a 50–50 “Arnold Palmer” blend and then round it up or down. The third, Lagrangian Relaxation, turns impossibilities into mere penalties, teaching the art of bending the rules..
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Computer scientists would call this a ping attack or a “denial of service attack: give a system an overwhelming number of trivial things to do, and the important things get lost in the chaos.