Data Famous Quotes

In the 17th century, the French statesman Cardinal Richelieu famously said, “Show me six lines written by the most honest man in the world, and I will find enough therein to hang him.” Lavrentiy Beria, head of Joseph Stalin’s secret police in the old Soviet Union, declared, “Show me the man, and I’ll show you the crime.” Both were saying the same thing: if you have enough data about someone, you can find sufficient evidence to find him guilty of something.

Simone de Beauvoir made it most famously when in 1949 she wrote, ‘humanity is male and man defines woman not in herself, but as relative to him; she is not regarded as an autonomous being. [. . .] He is the Subject, he is the Absolute – she is the Other.

In security, you are only as secure as the weakest link.

In the midst of this culture of openness and sharing, we need to think carefully about the information we're volunteering to the world. Sometimes the world is listening.

Frankly, the overwhelming majority of academics have ignored the data explosion caused by the digital age. The world’s most famous sex researchers stick with the tried and true. They ask a few hundred subjects about their desires; they don’t ask sites like PornHub for their data. The world’s most famous linguists analyze individual texts; they largely ignore the patterns revealed in billions of books. The methodologies taught to graduate students in psychology, political science, and sociology have been, for the most part, untouched by the digital revolution. The broad, mostly unexplored terrain opened by the data explosion has been left to a small number of forward-thinking professors, rebellious grad students, and hobbyists. That will change.

Blaise Pascal, the famous French mathematician and physicist, wrote in Lettres Provinciales (translated), “I have made this longer than usual because I have not had time to make it shorter.

Is there something to the notion "Let me sleep on it."? Mountains of data says there is. For example, Mendeleyev - the creator of the Periodic Table of Elements - says that he came up with this idea in his sleep. Contemplating the nature of the universe while playing Solitaire one evening, he nodded off. When he awoke, he knew how all the atoms in the universe were organised, and he promptly created his famous table. Interestingly, he organised the atoms in repeating groups of seven, just the way you play Solitaire.

BERLIN, October 29 I’ve been looking into what Germans are reading these dark days. Among novels the three best-sellers are: (1) Gone with the Wind, translated as Vom Winde Verweht—literally “From the Wind Blown About”; (2) Cronin’s Citadel; (3) Beyond Sing the Woods, by Trygve Gulbranssen, a young Norwegian author. Note that all three novels are by foreign authors, one by an Englishman. Most sought-after non-fiction books are: (1) The Coloured Front, an anonymous study of the white-versus-Negro problem; (2) Look Up the Subject of England, a propaganda book about England; (3) Der totale Krieg, Ludendorff’s famous book about the Total War—very timely now; (4) Fifty Years of Germany, by Sven Hedin, the Swedish explorer and friend of Hitler; (5) So This is Poland, by von Oertzen, data on Poland, first published in 1928. Three

What was once an anonymous medium where anyone could be anyone—where, in the words of the famous New Yorker cartoon, nobody knows you’re a dog—is now a tool for soliciting and analyzing our personal data. According to one Wall Street Journal study, the top fifty Internet sites, from CNN to Yahoo to MSN, install an average of 64 data-laden cookies and personal tracking beacons each. Search for a word like “depression” on Dictionary.com, and the site installs up to 223 tracking cookies and beacons on your computer so that other Web sites can target you with antidepressants. Share an article about cooking on ABC News, and you may be chased around the Web by ads for Teflon-coated pots. Open—even for an instant—a page listing signs that your spouse may be cheating and prepare to be haunted with DNA paternity-test ads. The new Internet doesn’t just know you’re a dog; it knows your breed and wants to sell you a bowl of premium kibble.

The importance of the base rate was made famous by the psychologist Daniel Kahneman, who coined the phrase “the outside view and the inside view.” The inside view means looking at the specific case in front of you: this couple. The outside view requires you to look at a more general “comparison class” of cases—here, the comparison class is all married couples. (The outside view needn’t be statistical, but it often will be.)

The sphere to end all spheres—the largest and most perfect of them all—is the entire observable universe. In every direction we look, galaxies recede from us at speeds proportional to their distance. As we saw in the first few chapters, this is the famous signature of an expanding universe, discovered by Edwin Hubble in 1929. When you combine Einstein’s relativity and the velocity of light and the expanding universe and the spatial dilution of mass and energy as a consequence of that expansion, there is a distance in every direction from us where the recession velocity for a galaxy equals the speed of light. At this distance and beyond, light from all luminous objects loses all its energy before reaching us. The universe beyond this spherical “edge” is thus rendered invisible and, as far as we know, unknowable. There’s a variation of the ever-popular multiverse idea in which the multiple universes that comprise it are not separate universes entirely, but isolated, non-interacting pockets of space within one continuous fabric of space-time—like multiple ships at sea, far enough away from one another so that their circular horizons do not intersect. As far as any one ship is concerned (without further data), it’s the only ship on the ocean, yet they all share the same body of water.

Experts can sound pretty impressive, of course, especially when they bolster their claims by citing their years of training and experience in a field. Yet hundreds of studies have shown that, compared to predictions based on actuarial data, predictions based on an expert's years of training and personal experience are rarely better than chance. But when an expert is wrong, the centerpiece of his or her professional identity is threatened. Therefore, dissonance theory predicts that the more self-confident and famous experts are, the less likely they will be to admit mistakes. And that is just what Tetlock found. Experts reduced the dissonance caused by their failed forecasts by coming up with explanations of why they would have been right "if only" - if only that improbable calamity had not intervened; if only the timing of events had been different; if only blah-blah-blah.

White women had a fundamental role in building this new, more combative Christian right. Their attitudes and political viewpoints came as a reaction to social change. It would seem that white evangelical women would’ve been deeply offended by Trump’s multiple marriages, documented and highly public infidelities, and, most famously, the Access Hollywood tape released in 2016 of a dialogue between television host Billy Bush and Donald Trump: Trump: You know I’m automatically attracted to be beautiful women—I just start kissing them. It’s like a magnet. Just kiss. I don’t even wait. And when you’re a star, they let you do it. You can do anything Bush: Whatever you want. Trump: Grab ‘em by the pussy. You can do anything. Yet data show that a majority of white evangelical women voted for Trump. Moreover, the higher their church attendance, the more likely they were to vote for Trump…

Lazlo Bock, senior vice president of people operations at Google, made the following comments in an interview published by the New York Times in June 2013: “One of the things we’ve seen from all our data crunching is that G.P.A.’s (grade point averages) are worthless as a criteria for hiring, and test scores are worthless. Google famously used to ask everyone for a transcript and G.P.A.’s and test scores, but we don’t anymore…. We found that they don’t predict anything. What’s interesting is the proportion of people without any college education at Google has increased over time as well. So we have teams where you have 14 percent of the team made up of people who’ve never gone to college.” Doing well in college—earning high test scores and grades—has no measurable correlation with becoming an effective worker or manager.  This is incontrovertible evidence that the entire Higher Education system is detached from the real economy: excelling in higher education has little discernible correlation to real-world skills or performance.

Things have becone even more mysterious. We have recently discovered that when we make observations at still larger scales, corresponding to billions of light-years, the equations of general relativity are not satisfied even when the dark matter is added in. The expansion of the universe, set in motion by the big bang some 13.7 billion years ago, appears to be accelerating, whereas, given the observed matter plus the calculated amount of dark matter, it should be doing the opposite-decelerating. Again there are two possible explanations. General relativity could simply be wrong. It has been verified precisely only within our solar system and nearby systems in our own galaxy. Perhaps when one gets to a scale comparable to the size of the whole universe, general relativity is simply no longer applicable. Or there is a new form of matter-or energy (recall Einstein's famous equation E=mc^2, showing the equivalence of energy and mass)-that becomes relevant on these very large scales: That is, this new form of energy affects only the expansion of the universe. To do this, it cannot clump around galaxies or even clusters of galaxies. This strange new energy, which we have postulated to fit the data, is called the dark energy.

[THE DAILY BREATH] Blaise Pascal, the famous mathematician, once said: "To those who wish to see, God gives them sufficient light. To those who doesn't wish to see, God gives them sufficient darkness." Seeing the Truth is a choice. Listening to my words is a choice. Healing is a choice. If want scientific evidence about the existence of God, there is a wealth of data to support it. Dr. Jeffrey Long, M.D. used the best scientific techniques available today to study more than 4,000 people who had near-death experiences and found themselves face to face with our Heavenly Father. Read the book "God and the Afterlife" and you will find it. If you want scientific evidence about Jesus being the Son of God, Lee Strobel, an atheist investigative journalist discovered it. Read the book "The Case for Christ" and you will find it. If you want scientific evidence about Jesus still healing today, study the ministries of Dr. Charles Ndifon, T.L. Osborn, Kathryn Kuhlman among others, and you will find it. But most importantly, if you want to fill the emptiness within you, and experience the perfect love, mercy and forgiveness, if you want to live in the peace of our Heavenly Father, give your body, your mind and your heart to Christ. Give your life to Jesus. The empty place you feel in your heart is reserved only for the spirit of Christ and nothing from this world will fill it. Look up to heaven, behold Jesus and Live.

Moore’s Law, the rule of thumb in the technology industry, tells us that processor chips—the small circuit boards that form the backbone of every computing device—double in speed every eighteen months. That means a computer in 2025 will be sixty-four times faster than it is in 2013. Another predictive law, this one of photonics (regarding the transmission of information), tells us that the amount of data coming out of fiber-optic cables, the fastest form of connectivity, doubles roughly every nine months. Even if these laws have natural limits, the promise of exponential growth unleashes possibilities in graphics and virtual reality that will make the online experience as real as real life, or perhaps even better. Imagine having the holodeck from the world of Star Trek, which was a fully immersive virtual-reality environment for those aboard a ship, but this one is able to both project a beach landscape and re-create a famous Elvis Presley performance in front of your eyes. Indeed, the next moments in our technological evolution promise to turn a host of popular science-fiction concepts into science facts: driverless cars, thought-controlled robotic motion, artificial intelligence (AI) and fully integrated augmented reality, which promises a visual overlay of digital information onto our physical environment. Such developments will join with and enhance elements of our natural world. This is our future, and these remarkable things are already beginning to take shape. That is what makes working in the technology industry so exciting today. It’s not just because we have a chance to invent and build amazing new devices or because of the scale of technological and intellectual challenges we will try to conquer; it’s because of what these developments will mean for the world.

A famous British writer is revealed to be the author of an obscure mystery novel. An immigrant is granted asylum when authorities verify he wrote anonymous articles critical of his home country. And a man is convicted of murder when he’s connected to messages painted at the crime scene. The common element in these seemingly disparate cases is “forensic linguistics”—an investigative technique that helps experts determine authorship by identifying quirks in a writer’s style. Advances in computer technology can now parse text with ever-finer accuracy. Consider the recent outing of Harry Potter author J.K. Rowling as the writer of The Cuckoo’s Calling , a crime novel she published under the pen name Robert Galbraith. England’s Sunday Times , responding to an anonymous tip that Rowling was the book’s real author, hired Duquesne University’s Patrick Juola to analyze the text of Cuckoo , using software that he had spent over a decade refining. One of Juola’s tests examined sequences of adjacent words, while another zoomed in on sequences of characters; a third test tallied the most common words, while a fourth examined the author’s preference for long or short words. Juola wound up with a linguistic fingerprint—hard data on the author’s stylistic quirks. He then ran the same tests on four other books: The Casual Vacancy , Rowling’s first post-Harry Potter novel, plus three stylistically similar crime novels by other female writers. Juola concluded that Rowling was the most likely author of The Cuckoo’s Calling , since she was the only one whose writing style showed up as the closest or second-closest match in each of the tests. After consulting an Oxford linguist and receiving a concurring opinion, the newspaper confronted Rowling, who confessed. Juola completed his analysis in about half an hour. By contrast, in the early 1960s, it had taken a team of two statisticians—using what was then a state-of-the-art, high-speed computer at MIT—three years to complete a project to reveal who wrote 12 unsigned Federalist Papers. Robert Leonard, who heads the forensic linguistics program at Hofstra University, has also made a career out of determining authorship. Certified to serve as an expert witness in 13 states, he has presented evidence in cases such as that of Christopher Coleman, who was arrested in 2009 for murdering his family in Waterloo, Illinois. Leonard testified that Coleman’s writing style matched threats spray-painted at his family’s home (photo, left). Coleman was convicted and is serving a life sentence. Since forensic linguists deal in probabilities, not certainties, it is all the more essential to further refine this field of study, experts say. “There have been cases where it was my impression that the evidence on which people were freed or convicted was iffy in one way or another,” says Edward Finegan, president of the International Association of Forensic Linguists. Vanderbilt law professor Edward Cheng, an expert on the reliability of forensic evidence, says that linguistic analysis is best used when only a handful of people could have written a given text. As forensic linguistics continues to make headlines, criminals may realize the importance of choosing their words carefully. And some worry that software also can be used to obscure distinctive written styles. “Anything that you can identify to analyze,” says Juola, “I can identify and try to hide.

Correlation is enough,” 2 then-Wired editor in chief Chris Anderson famously declared in 2008. We can, he implied, solve innovation problems by the sheer brute force of the data deluge. Ever since Michael Lewis chronicled the Oakland A’s unlikely success in Moneyball (who knew on-base percentage was a better indicator of offensive success than batting averages?), organizations have been trying to find the Moneyball equivalent of customer data that will lead to innovation success. Yet few have. Innovation processes in many companies are structured and disciplined, and the talent applying them is highly skilled. There are careful stage-gates, rapid iterations, and checks and balances built into most organizations’ innovation processes. Risks are carefully calculated and mitigated. Principles like six-sigma have pervaded innovation process design so we now have precise measurements and strict requirements for new products to meet at each stage of their development. From the outside, it looks like companies have mastered an awfully precise, scientific process. But for most of them, innovation is still painfully hit or miss. And worst of all, all this activity gives the illusion of progress, without actually causing it. Companies are spending exponentially more to achieve only modest incremental innovations while completely missing the mark on the breakthrough innovations critical to long-term, sustainable growth. As Yogi Berra famously observed: “We’re lost, but we’re making good time!” What’s gone so wrong? Here is the fundamental problem: the masses and masses of data that companies accumulate are not organized in a way that enables them to reliably predict which ideas will succeed. Instead the data is along the lines of “this customer looks like that one,” “this product has similar performance attributes as that one,” and “these people behaved the same way in the past,” or “68 percent of customers say they prefer version A over version B.” None of that data, however, actually tells you why customers make the choices that they do.

A famous 1978 paper that claimed that winning the lottery does not make you happy has largely been debunked.

Research from Brunel University shows that chess students who trained with coaches increased on average 168 points in their national ratings versus those who didn’t. Though long hours of deliberate practice are unavoidable in the cognitively complex arena of chess, the presence of a coach for mentorship gives players a clear advantage. Chess prodigy Joshua Waitzkin (the subject of the film Searching for Bobby Fischer) for example, accelerated his career when national chess master Bruce Pandolfini discovered him playing chess in Washington Square Park in New York as a boy. Pandolfini coached young Waitzkin one on one, and the boy won a slew of chess championships, setting a world record at an implausibly young age. Business research backs this up, too. Analysis shows that entrepreneurs who have mentors end up raising seven times as much capital for their businesses, and experience 3.5 times faster growth than those without mentors. And in fact, of the companies surveyed, few managed to scale a profitable business model without a mentor’s aid. Even Steve Jobs, the famously visionary and dictatorial founder of Apple, relied on mentors, such as former football coach and Intuit CEO Bill Campbell, to keep himself sharp. SO, DATA INDICATES THAT those who train with successful people who’ve “been there” tend to achieve success faster. The winning formula, it seems, is to seek out the world’s best and convince them to coach us. Except there’s one small wrinkle. That’s not quite true. We just held up Justin Bieber as an example of great, rapid-mentorship success. But since his rapid rise, he’s gotten into an increasing amount of trouble. Fights. DUIs. Resisting arrest. Drugs. At least one story about egging someone’s house. It appears that Bieber started unraveling nearly as quickly as he rocketed to Billboard number one. OK, first of all, Bieber’s young. He’s acting like the rock star he is. But his mentor, Usher, also got to Billboard number one at age 18, and he managed to dominate pop music for a decade without DUIs or egg-vandalism incidents. Could it be that Bieber missed something in the mentorship process? History, it turns out, is full of people who’ve been lucky enough to have amazing mentors and have stumbled anyway.

Minsky was an ardent supporter of the Cyc project, the most notorious failure in the history of AI. The goal of Cyc was to solve AI by entering into a computer all the necessary knowledge. When the project began in the 1980s, its leader, Doug Lenat, confidently predicted success within a decade. Thirty years later, Cyc continues to grow without end in sight, and commonsense reasoning still eludes it. Ironically, Lenat has belatedly embraced populating Cyc by mining the web, not because Cyc can read, but because there’s no other way. Even if by some miracle we managed to finish coding up all the necessary pieces, our troubles would be just beginning. Over the years, a number of research groups have attempted to build complete intelligent agents by putting together algorithms for vision, speech recognition, language understanding, reasoning, planning, navigation, manipulation, and so on. Without a unifying framework, these attempts soon hit an insurmountable wall of complexity: too many moving parts, too many interactions, too many bugs for poor human software engineers to cope with. Knowledge engineers believe AI is just an engineering problem, but we have not yet reached the point where engineering can take us the rest of the way. In 1962, when Kennedy gave his famous moon-shot speech, going to the moon was an engineering problem. In 1662, it wasn’t, and that’s closer to where AI is today. In industry, there’s no sign that knowledge engineering will ever be able to compete with machine learning outside of a few niche areas. Why pay experts to slowly and painfully encode knowledge into a form computers can understand, when you can extract it from data at a fraction of the cost? What about all the things the experts don’t know but you can discover from data? And when data is not available, the cost of knowledge engineering seldom exceeds the benefit. Imagine if farmers had to engineer each cornstalk in turn, instead of sowing the seeds and letting them grow: we would all starve.

In a famous passage of his book The Sciences of the Artificial, AI pioneer and Nobel laureate Herbert Simon asked us to consider an ant laboriously making its way home across a beach. The ant’s path is complex, not because the ant itself is complex but because the environment is full of dunelets to climb and pebbles to get around. If we tried to model the ant by programming in every possible path, we’d be doomed. Similarly, in machine learning the complexity is in the data; all the Master Algorithm has to do is assimilate it, so we shouldn’t be surprised if it turns out to be simple. The human hand is simple—four fingers, one opposable thumb—and yet it can make and use an infinite variety of tools. The Master Algorithm is to algorithms what the hand is to pens, swords, screwdrivers, and forks.

But machine learning is the art of making false assumptions and getting away with it. As the statistician George Box famously put it: “All models are wrong, but some are useful.” An oversimplified model that you have enough data to estimate is better than a perfect one that you don’t.

Researchers may have some conscious or unconscious bias, either because of a strongly held prior belief or because a positive finding would be better for their career. (No one ever gets rich or famous by proving what doesn't cause cancer.)

More sophisticated methods exist, of course. A potentially more powerful method is collaborative filtering. It gathers data about what users have bought in the past and uses AI to predict what people are likely to buy in the future. These methods can use both explicit information, like a customer’s ratings of the options, and implicit information, like whether or not they finished a specific program on Netflix. Most famously, perhaps, collaborative filtering is used by Amazon in generating “People who bought this also bought . . .” listings. Collaborative filtering requires a large set of past user behavior to make predictions. This is the heart of suggestions made by Apple Music, “who to follow” suggestions on Twitter, and matches on Tinder. Yes, Tinder apparently changes the people it will show you based on your swipes. Swiping right will change who you see in the future. It’s important to realize that, in its pure form, collaborative filtering doesn’t use in-depth information about the options themselves. When Apple Music recommends a tune, it knows nothing about the song’s tempo, beat, lyrics, or instrumentation. It simply knows that people who are like you like that song too.

But if we have carefully chosen indicators that characterize an administrative unit and watch them closely, we are ready to apply the methods of factory control to administrative work. We can use de facto standards, inferred from the trend data, to forecast the number of people needed to accomplish various anticipated tasks. By rigorous application of the principles of forecasting, manpower can be reassigned from one area to another, and the headcount made to match the forecasted growth or decline in administrative activity. Without rigor, the staffing of administrative units would always be left at its highest level and, given Parkinson’s famous law, people would find ways to let whatever they’re doing fill the time available for its completion.

Правило номер 1 искусства быть невидимым: никогда не связывайте свою анонимную онлайн-личность с реальной. Никогда не делайте этого

Обеспечение безопасности сводится к созданию достаточного количества препятствий, чтобы атаующий отказался от дальнейших попыток и выбрал другую цель

For example, perhaps there is some off-chain event of significant importance where you want to store it for the record. Suppose it’s the famous photo of Stalin with his cronies, because you anticipate the rewriting of history. The proof-of-existence technique we’re about to describe wouldn’t directly be able to prove the data of the file was real, but you could establish the metadata on the file — the who, what, and when — to a future observer. Specifically, given a proof-of-existence, a future observer would be able to confirm that a given digital signature (who) put a given hash of a photo (what) on chain at a given time (when). That future observer might well suspect the photo could still be fake, but they’d know it’d have to be faked at that precise time by the party controlling that wallet. And the evidence would be on-chain years before the airbrushed official photo of Stalin was released. That’s implausible under many models. Who’d fake something so specific years in advance? It’d be more likely the official photo was fake than the proof-of-existence.

You might not have anything to hide, my friend. But you have everything to protect.

I imagine that if I had been a male student my name might have been mentioned in class or that the professor might have encouraged my career in computer science, or perhaps offered me an opportunity in his or a colleague’s lab. This is why I get deeply angry when famous men (like Larry Summers, whom I will come to below) espouse the idea that women as a group are innately less good at science than men but say that of course they do not discriminate against individual talented women. They fail to miss the basic point that in the face of pervasive negative stereotyping, talented women will not be recognized. Such negative stereotyping is not supported by any data and is deeply harmful to all women

Famous designer Erik Spiekermann released a font called Axel that he designed for on screen use in spreadsheets.

I used Harvard’s computer system only once as an undergraduate, to run regressions for my senior thesis on the economics of spousal abuse. The data was stored on large, heavy magnetic tapes that I had to lug in big boxes across campus, cursing the entire way and arriving in a sweaty mess at the sole computer center, which was populated exclusively with male students. I then had to stay up all night spinning the tapes to input the data. When I tried to execute my final calculations, I took down the entire system. That’s right. Years before Mark famously crashed that same Harvard system, I beat him to it.

The process of creating .jpgs is synonymous with the process of throwing away information. 12-bits of data per channel from the sensor gets squeezed into 8 bits of data per channel (giving up some tonality and fine shades of color). A little bit of dynamic range gets lost too.  Then Lots of visual information that the human brain cannot perceive gets thrown away, which is what’s responsible for JPG’s famously small size.  If there is a lot of high-frequency detail in the image, then that gets replaced by what’s called a .jpg compression artifact (which I describe in a couple of sections).  Then the compressed .jpg image file is written to the memory card, and then the raw information from which the .jpg was produced is discarded (unless you were wise enough to shoot in RAW + JPG mode). 

For example, every year, I rent Intuit’s TurboTax so I can do my income taxes. I pay for something I only need for a few weeks in February even though it holds my data for the entire year. That is because it has my data from the previous year (and for years before that). It simply asks if my financial situation has changed or if I have unique needs for a given tax year. It even has built-in, crowd-based support to help me when I get stuck. TurboTax meets many of the lovability requirements. It solves my problem, meets needs I did not know I had, makes my life easier, and adapts as my circumstances change. Best of all, I pay a reasonable price to rent it every year. But how does Intuit really know what I need? Well, Intuit is famous for a program they call Follow Me Home. It sounds exactly like what it is — a way to observe customers in their homes or offices in order to understand how they actually use Intuit’s products. The founding team used Follow Me Home as a way to help their teams get an immersive look at what customers liked and what they needed, as well as what worked and what did not work. By observing customers in their own spaces, the Intuit team was able to see how often customers were interrupted while trying to use their product, or if they started on one device and finished the task on another. They were able to funnel that information back to their development team to make updates in subsequent releases. It is important to note that they were not following customers home to look for bugs in the product. No, they had a deeper purpose — to truly understand the experience of their customers and if their products were making their work and life easier. That deep commitment to understanding customers helped Intuit find elegant ways to help them. It is a simple concept and one that more product builders would benefit from.

donated skeletal collection; one more skull was just a final drop in the bucket. Megan and Todd Malone, a CT technician in the Radiology Department at UT Medical Center, ran skull 05-01 through the scanner, faceup, in a box that was packed with foam peanuts to hold it steady. Megan FedExed the scans to Quantico, where Diana and Phil Williams ran them through the experimental software. It was with high hopes, shortly after the scan, that I studied the computer screen showing the features ReFace had overlaid, with mathematical precision, atop the CT scan of Maybe-Leoma’s skull. Surely this image, I thought—the fruit of several years of collaboration by computer scientists, forensic artists, and anthropologists—would clearly settle the question of 05-01’s identity: Was she Leoma or was she Not-Leoma? Instead, the image merely amplified the question. The flesh-toned image on the screen—eyes closed, the features impassive—could have been a department-store mannequin, or a sphinx. There was nothing in the image, no matter how I rotated it in three dimensions, that said, “I am Leoma.” Nor was there anything that said, “I am not Leoma.” To borrow Winston Churchill’s famous description of Russia, the masklike face on the screen was “a riddle wrapped in a mystery inside an enigma.” Between the scan, the software, and the tissue-depth data that the software merged with the

There’s a quote from the famous physicist Niels Bohr, who posits that the way you become an expert in a field is to make every mistake possible in that field.

Yuguo fell apart, into a thousand little pieces. He felt it happen, fragments of his mind detaching from the rest, splitting off, becoming their own, being mapped by Nexus. Here was Yuguo’s knowledge of coding, his comprehension of data structures, of objects and methods, of intents and game players, of threads and loops and conditions. Here was football Yuguo, the precise way his left foot grounded into the grass and his hips swiveled and his arm balanced as his right foot shot forward to kick the checked ball at the goal. Here was Yuguo’s shy lust for girls, the patterns his eyes drew over their curves when he saw them, the anxiety that struck him dumb when they were near. Here was Yuguo’s despair that had led him to this room, his quiet dread that his country and the world were getting worse instead of better, that the future was one of slow strangulation at the electronic hands of smiling tame AIs with famous faces, their forked tongues lapping out of the viewscreens to feed saccharine to the masses, the old men who’d always ruled China laughing and holding their leashes. Here were the words a young woman had said to him just minutes ago. “Critical mass. Weak apart, strong together.” Here were her eyes, fiery eyes, hanging in space. Here was her name: Lifen. Then those pieces fell apart, into smaller pieces, which fell apart into fragments even smaller: Yuguo’s sensation of red. Yuguo’s concept of 1 and 0. Yuguo’s left thumb. The sound in Yuguo’s head when he heard the third note of his favorite pop song. Yuguo’s yes. Yuguo’s no. Yuguo’s and. Yuguo’s or. Yuguo’s xor. Yuguo’s now. Yuguo’s future. Yuguo’s past. He could see himself now. He was a golden statue of Yuguo, immobile, one foot in front of the other, standing in a space of white light. But the statue wasn’t solid, it was made of grains, millions of grains, flecks of gold dust, millions of parts of him. And as he watched they were separating, pulling gradually apart, so that he was no longer a single entity but a cloud, a fog, a fog of Yuguo, and if a strong wind came, he would just blow away, and if the pieces split any more he knew there wouldn’t be any such thing as Yuguo left at all. Yuguo’s fear. Yuguo’s end. And then the pieces rushed together, and he was inside that statue, he was that statue, and he was all of it, 1 and 0, yes and no, future and past, sound and sight, football and coding. He was all of it. He was whole. He was a mind. I’m Yuguo, he realized. I’m him. I’m me. I’m Yuguo! His eyes snapped open. He was in his body. His body made of molten gold. No, not gold, flesh and blood.

At the young age of 15, Gates went into business with Paul Allen. They developed a program for monitoring Seattle’s traffic patterns, called Traf-o-Data, which earned them around $20,000.

Over 100 years ago, John Wanamaker said the famous line: “Half the money I spend on marketing is wasted—the problem is I don’t know which half.

Petrov was the commander in charge when satellite data indicated there were five American ICBMs on their way to strike Moscow with nuclear weapons. For reasons having to do with human intuition, Petrov became suspicious of that attack information. Years later, he told Washington Post reporter David Hoffman what he was thinking at the time. “I had a funny feeling in my gut,” Petrov said, asking himself, Who starts a nuclear war against another superpower with just five ICBMs? In 1983, Petrov made the decision to interpret the early-warning signal as a “false alarm,” he said, thereby not sending a report up the chain of command. For his well-placed skepticism, Lieutenant Colonel Stanislav Petrov famously became known as “the man who saved the world from nuclear war.

The murder of Greg Faull remains unsolved. McAfee now lives in Tennessee, and in 2015 he decided to run for president to advocate for more cyberfriendly policies in the US government. He doesn’t blog nearly as often nowadays.

There’s another level at which attention operates, this has to do with leadership, I argue that leaders need three kinds of focus, to be really effective, the first is an inner focus, let me tell you about a case that’s actually from the annals of neurology, there was a corporate lawyer, who unfortunately had a small prefrontal brain tumour, it was discovered early, operated successfully, after the surgery though it was a very puzzling picture, because he was absolutely as smart as he had been before, a very high IQ, no problem with attention or memory, but he couldn’t do his job anymore, he couldn’t do any job, in fact he ended up out of work, his wife left him, he lost his home, he’s living in his brother spare bedroom and in despair he went to see a famous neurologist named Antonio Damasio. Damasio specialized in the circuitry between the prefrontal area which is where we consciously pay attention to what matters now, where we make decisions, where we learn and the emotional centers in the midbrain, particularly the amygdala, which is our radar for danger, it triggers our strong emotions. They had cut the connection between the prefrontal area and emotional centers and Damasio at first was puzzled, he realized that this fellow on every neurological test was perfectly fine but something was wrong, then he got a clue, he asked the lawyer when should we have our next appointment and he realized the lawyer could give him the rational pros and cons of every hour for the next two weeks, but he didn’t know which is best. And Damasio says when we’re making a decision any decision, when to have the next appointment, should I leave my job for another one, what strategy should we follow, going into the future, should I marry this fellow compared to all the other fellows, those are decisions that require we draw on our entire life experience and the circuitry that collects that life experience is very base brain, it’s very ancient in the brain, and it has no direct connection to the part of the brain that thinks in words, it has very rich connectivity to the gastro- intestinal tract, to the gut, so we get a gut feeling, feels right, doesn’t feel right. Damasio calls them somatic markers, it’s a language of the body and the ability to tune into this is extremely important because this is valuable data too - they did a study of Californian entrepreneurs and asked them “how do you make your decisions?”, these are people who built a business from nothing to hundreds of millions or billions of dollars, and they more or less said the same strategy “I am a voracious gatherer of information, I want to see the numbers, but if it doesn’t feel right, I won’t go ahead with the deal”. They’re tuning into the gut feeling. I know someone, I grew up in farm region of California, the Central Valley and my high school had a rival high school in the next town and I met someone who went to the other high school, he was not a good student, he almost failed, came close to not graduating high school, he went to a two-year college, a community college, found his way into film, which he loved and got into a film school, in film school his student project caught the eye of a director, who asked him to become an assistant and he did so well at that the director arranged for him to direct his own film, someone else’s script, he did so well at that they let him direct a script that he had written and that film did surprisingly well, so the studio that financed that film said if you want to do another one, we will back you. And he, however, hated the way the studio edited the film, he felt he was a creative artist and they had butchered his art. He said I am gonna do the film on my own, I’m gonna finance it myself, everyone in the film business that he knew said this is a huge mistake, you shouldn’t do this, but he went ahead, then he ran out of money, had to go to eleven banks before he could get a loan, he managed to finish the film, you may have seen

Venture capitalists and investors have bought into the media-driven narrative that younger people are more likely to build great companies. Vinod Khosla, a cofounder of Sun Microsystems and venture capitalist, said, “People under 35 are the people who make change happen . . . people over 45 basically die in terms of new ideas.” Paul Graham, the founder of Y Combinator, the famous start-up accelerator, said that, when a founder is over the age of thirty-two, investors “start to be a little skeptical.” Zuckerberg himself famously said, with his characteristic absence of tact, “Young people are just smarter.” But, it turns out, when it comes to age, the entrepreneurs we learn about in the media are not representative. In a pathbreaking study, a team of economists—Pierre Azoulay, Benjamin F. Jones, J. Daniel Kim, and Javier Miranda (henceforth referred to as AJKM)—analyzed the age of the founder of every business created in the United States between the years 2007 and 2014. Their study included some 2.7 million entrepreneurs, a far broader and more representative sample than the dozens featured in business magazines. The researchers found that the average age of a business founder in the United States is 41.9 years old—in other words, more than a decade older than the average age of founders featured in the media. And older people don’t just start businesses more than many of us realize; they also succeed at creating highly profitable businesses more often than their younger peers do. AJKM used various metrics of success for a business, including staying in business for longer and ranking among the top firms in revenue and employees. They discovered that older founders consistently had higher probabilities of success, at least until the age of sixty.

Second, when quality is hard to judge, there is a Da Vinci Effect, which was first coined in a blog post by Jeff Alworth in 2017. The Da Vinci Effect says that the success of an artist begets more success for that artist. People are willing to pay more for the work of an artist who is already famous. Indeed, there are many examples of pieces of art that dramatically changed in value when experts changed their mind regarding who created it. Consider, for example, the Salvator Mundi, a depiction of Jesus Christ. In 2005, it was sold for less than $10,000. In 2017, a mere twelve years later, it was sold for $450.3 million, the highest price ever for a piece of art. What caused the price to rise so much in such a short time? In the in-between years, art experts became convinced that the painting had been created by Leonardo da Vinci. In other words, the same painting is worth 45,000 times more just because Da Vinci drew it.

The insatiable need for more processing power -- ideally, located as close as possible to the user but, at the very least, in nearby indus­trial server farms -- invariably leads to a third option: decentralized computing. With so many powerful and often inactive devices in the homes and hands of consumers, near other homes and hands, it feels inevitable that we'd develop systems to share in their mostly idle pro­cessing power. "Culturally, at least, the idea of collectively shared but privately owned infrastructure is already well understood. Anyone who installs solar panels at their home can sell excess power to their local grid (and, indirectly, to their neighbor). Elon Musk touts a future in which your Tesla earns you rent as a self-driving car when you're not using it yourself -- better than just being parked in your garage for 99% of its life. "As early as the 1990s programs emerged for distributed computing using everyday consumer hardware. One of the most famous exam­ples is the University of California, Berkeley's SETl@HOME, wherein consumers would volunteer use of their home computers to power the search for alien life. Sweeney has highlighted that one of the items on his 'to-do list' for the first-person shooter Unreal Tournament 1, which shipped in 1998, was 'to enable game servers to talk to each other so we can just have an unbounded number of players in a single game session.' Nearly 20 years later, however, Sweeney admitted that goal 'seems to still be on our wish list.' "Although the technology to split GPUs and share non-data cen­ter CPUs is nascent, some believe that blockchains provide both the technological mechanism for decentralized computing as well as its economic model. The idea is that owners of underutilized CPUs and GPUs would be 'paid' in some cryptocurrency for the use of their processing capabilities. There might even be a live auction for access to these resources, either those with 'jobs' bidding for access or those with capacity bidding on jobs. "Could such a marketplace provide some of the massive amounts of processing capacity that will be required by the Metaverse? Imagine, as you navigate immersive spaces, your account continuously bidding out the necessary computing tasks to mobile devices held but unused by people near you, perhaps people walking down the street next to you, to render or animate the experiences you encounter. Later, when you’re not using your own devices, you would be earning tokens as they return the favor. Proponents of this crypto-exchange concept see it as an inevitable feature of all future microchips. Every computer, no matter how small, would be designed to be auctioning off any spare cycles at all times. Billions of dynamically arrayed processors will power the deep compute cycles of event the largest industrial customers and provide the ultimate and infinite computing mesh that enables the Metaverse.

This hardened response to those on the “other team” is not an invention of modern American politics. It seems to be hardwired into the circuitry of our brains. The Old Testament is filled with stories of sometimes deadly tribalism, and scientific data gives us insight into why that happens. In 1968, elementary school teacher Jane Elliott conducted a famous experiment with her students in the days after the assassination of Dr. Martin Luther King Jr. She divided the class by eye color. The brown-eyed children were told they were better. They were the “in-group.” The blue-eyed children were told they were less than the brown-eyed children—hence becoming the “out-group.” Suddenly, former classmates who had once played happily side by side were taunting and torturing one another on the playground. Lest we assign greater morality to the “out-group,” the blue-eyed children were just as quick to attack the brown-eyed children once the roles were reversed.6

One important reason that philosophers should take Nietzsche seriously is because he seems to have gotten, at least in broad contours, many points about human moral psychology right. Consider: (1) Nietzsche holds that heritable type-facts are central determinants of personality and morally significant behaviors, a claim well supported by extensive empirical findings in behavioral genetics. (2) Nietzsche claims that consciousness is a “surface” and that “the greatest part of conscious thought must still be attributed to [non-conscious] instinctive activity,” theses overwhelmingly vindicated by recent work by psychologists on the role of the unconscious (e.g., Wilson 2002) and by philosophers who have produced synthetic meta-analyses of work on consciousness in psychology and neuroscience (e.g., Rosenthal 2008). (3) Nietzsche claims that moral judgments are post-hoc rationalizations of feelings that have an antecedent source, and thus are not the outcome of rational reflection or discursiveness, a conclusion in sync with the findings of the ascendent “social intuitionism” in the empirical moral psychology of Jonathan Haidt (2001) and others. (4) Nietzsche argues that free will is an “illusion,” that our conscious experience of willing is itself the causal product of non-conscious forces, a view recently defended by the psychologist Daniel Wegner (2002), who, in turn, synthesiyes a large body of empirical literature, including the famous neurophysical data about “willing” collected by Benjamin Libet.

В определенный момент нас может начать беспокоить то, что правительство, работодатели, начальники, учителя и родители имеют слишком большой доступ к нашей личной жизни. Но поскольку границы этого доступа расширялись постепенно, поскольку мы принимали каждую цифровую технологию, которая делала нашу жизнь чуточку удобнее, не задумываясь о том, как это отразится на нашей приватности, теперь повернуть все вспять становится все труднее и труднее. Кроме того, кто из нас готов отказаться от своих игрушек? Жить в условиях тотального цифрового контроля со стороны государства опасно не столько тем, что кто-то занимается сбором наших данных (с этим ничего не поделаешь), сколько тем, как используются собранные данные. Представьте себе, что дотошный полицейский или прокурор может сделать с собранным на вас обширным досье непроверенных данных, возможно, за последние несколько лет. Та информация, которая попала в ваше досье сейчас, часто вырванная из контекста, будет храниться вечно. Даже судья Верховного суда Стивен Брайер согласен с тем, что «любому человеку сложно заранее определить, в какой момент имеющиеся документы или факты его биографии могут показаться (обвинителю) важными в том или ином расследовании». Другими словами, выложенная кем-то в социальной сети Facebook ваша фотография в пьяном виде может оказаться наименьшей из ваших проблем. Возможно, вам кажется, что вам нечего скрывать, но как вы можете быть в этом уверены? Интернет-издание Wired опубликовало хорошо аргументированную статью уважаемого эксперта по безопасности Мокси Марлинспайка, который говорит о том, что в США федеральным преступлением может оказаться нечто, казалось бы, столь незначительное, как, например, держать дома маленького омара. «Не важно, купили ли вы его в продуктовом магазине или кто-то его вам подарил, жив он или мертв, нашли ли вы его уже после того, как он умер собственной смертью, или же убили его в результате самозащиты. Вас могут посадить в тюрьму только за то, что это омар». Суть в том, что в США существует множество незначительных законов, за соблюдением которых никто никогда не следил, а вы, возможно, нарушаете их и даже не подозреваете об этом. Но теперь при этом существует след из данных, служащих уликой против вас, и всего в нескольких кликах от любого, кому они могут понадобиться.

Why is web Hosting significant for your blog? At the point when a great many people start a blog, they're just pondering substance; they need to begin posting and building a local area as fast as could be expected. In doing as such, they skirt the imperative strides of guaranteeing that their blog is secure, possessed by them, and will stay in their control for the long stretch. Your site have is liable for guaranteeing that your blog is running at a speed that obliges traffic and is generally working as it ought to. At the point when you pursue a Hosting plan, you're basically purchasing land for your blog in one of the server farm servers, where your computerized data will be put away and made due. Web Hosting is the best way to guarantee that your blog will stay protected on the Internet. At the point when your blog's computerized data is under the management of a web have, the data is encoded, observed, and really focused on by a profoundly prepared help group. Navicosoft blog web Hosting We're extraordinarily glad for our reasonable, a-list Hosting administrations. We offer bloggers a scope of choices, which can all be custom fitted to meet your site needs and assumptions. Each Hosting plan accompanies a free SSL authentication a shield which scrambles your site information. Web Hosting choices for your blog For bloggers, Navicosoft offers an assortment of Hosting choices, each with interesting advantages and abilities. The web Hosting plan you picked will generally decide the degree to which your blog is safeguarded, the speed of your blog, and which stages will be accessible to you. Linux Hosting At the point when you pursue a cheap web Hosting plan with Navicosoft, you might see the expression "Linux." This is a working framework, a stage which utilizes a one-of-a-kind programming language, used to fabricate your blog or site. Linux is the most famous web Hosting working framework on the Internet. It's more affordable than different choices, and is known for blending steadiness with security. Without getting excessively specialized, it runs on programming dialects like Perl, PHP, and MySQL. These are open-source programming dialects leaned toward by engineers for the opportunity they offer, and their low functional expenses. For bloggers, Linux offers devices which simplify customization, and permit you to imaginatively draw in with the plan interaction. Shared Hosting Assuming you're simply beginning in the blogosphere, a common Hosting plan may be ideal. They require least specialized information, are exceptionally reasonable, and accompany a free SSL Certificate. Whenever you purchase a common Hosting plan, your blog is put away on a server with different web journals and sites. All sites and sites on that server share similar pool of assets. Shared Hosting is like moving into an occupied, protected, cheap area. The cost is brought down in light of the fact that everybody in the area is adding to similar arrangement of assets. Nonetheless, very much like in a bustling area, there are times when traffic gets, and during those times everybody in the area could move somewhat slower until it clears. Nonetheless, the distinction in speed is normally immaterial. At the point when you pursue a common Hosting plan with Navicosoft, you are ensured limitless site circle space, adaptable transfer speed, no less than 100 email addresses, free applications like WordPress (ideal for bloggers), and numerous different highlights. You likewise have limitless admittance to our all day, every day client assistance group. VPS Hosting VPS (Virtual Private Server) Hosting is a stage above shared Hosting plans. Whenever you purchase a VPS Hosting plan, you are basically getting a small server inside the bigger server. On the off chance that a common server is an occupied, protected, cheap area, a Virtual Private Server resembles a gated local area one region over.

hundreds of studies have shown that, compared to predictions based on actuarial data, predictions based on an expert’s years of training and personal experience are rarely better than chance. But when an expert is wrong, the centerpiece of his or her professional identity is threatened. Therefore, dissonance theory predicts that the more self-confident and famous experts are, the less likely they will be to admit mistakes.

One reason for this “dirty little secret” is the positive publication bias described in Chapter 7. If researchers and medical journals pay attention to positive findings and ignore negative findings, then they may well publish the one study that finds a drug effective and ignore the nineteen in which it has no effect. Some clinical trials may also have small samples (such as for a rare diseases), which magnifies the chances that random variation in the data will get more attention than it deserves. On top of that, researchers may have some conscious or unconscious bias, either because of a strongly held prior belief or because a positive finding would be better for their career. (No one ever gets rich or famous by proving what doesn’t cure cancer.)

Evolutionary biologist Stephen Jay Gould was diagnosed with a form of cancer that had a median survival time of eight months; he died of a different and unrelated kind of cancer twenty years later.3 Gould subsequently wrote a famous article called “The Median Isn’t the Message,” in which he argued that his scientific knowledge of statistics saved him from the erroneous conclusion that he would necessarily be dead in eight months.

In his essay “Self-Reliance,” Ralph Waldo Emerson famously wrote, “A foolish consistency is the hobgoblin of little minds”; in the same passage, he worried that individuals were getting stuck in “a reverence for our past act or word because the eyes of others have no other data for computing our orbit than our past acts, and we are loath to disappoint them.” Data. Computing. That was written in 1841,

This is (I suppose) a story. It draws a great deal on history; but as history is the lies the present tells in order to make sense of the past I have improved it where necessary. I have altered the places where facts, data, info, seem dull or inaccurate. I have quietly corrected errors in the calendar, adjusted flaws in world geography, now and then budged the border of a country, or changed the constitution of a nation. A wee postmodern Haussman, I have elegantly replanned some of the world's greatest cities, moving buildings to better sites, redesigning architecture, opening fresh views and fine urban prospects, redirecting the traffic. I've put statues in more splendid locations, usefully reorganised art galleries, cleaned, transferred or rehung famous paintings, staged entire new plays and operas. I have revised or edited some of our great books, and republished them. I have altered monuments, defaced icons, changed the street signs, occupied the railway station. In all this I have behaved just as history does itself, when it plots the world's advancing story in the great Book of Destiny above.

The British statistician George Box has become famous for his brief but invaluable aphorism: ‘All models are wrong, some are useful.’ This pithy statement was based on a lifetime spent bringing statistical expertise to industrial processes, which led Box to appreciate both the power of models, but also the danger of actually starting to believe in them too much.

At the end of the day, It's based on data. Try to upload as many videos as possible because, at the end of the say, it's all based on data. If you know a certain trend is working for you, then repeat it.

Right across the species, everything must be stored away and put under seal - including the famous genome - doubtless for the use of a later race, who will exploit it as fossil material. We shall ourselves, by the combined pressure of the mass of computer data and the continental drift, be transformed into a metamorphic deposit (the Unconscious already seems like a psychical residue of the Carboniferous). Right now, one has the impression the human race is merely turning in on itself and its origins, desperately gathering together its distress flares and dematerializing to transform itself into a message. But a message to whom? Everyone is looking for a safe area, some form of permanent plot that can eclipse existence as a primary abode and protect us from death. The unfortunate thing is there aren't even any plots held in perpetuity in the cemeteries any more.

You might have a sense of déjà vu about those first two types of dark data. In a famous news briefing, former U.S. Secretary of Defense Donald Rumsfeld nicely characterized them in a punchy sound bite, saying “there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns—the ones we don’t know we don’t know.”6 Rumsfeld attracted considerable media ridicule for that convoluted statement, but the criticism was unfair. What he said made very good sense and was certainly true.

The famous Andon cord is just one of their many tools that enable learning. When anyone encounters a problem, everyone is expected to ask for help at any time, even if it means stopping the entire assembly line. And they are thanked for doing so, because it is an opportunity to improve daily work.

Speaking at the Chaos Communication Congress, an annual computer hacker conference held in Berlin, Germany, Tobias Engel, founder of Sternraute, and Karsten Nohl, chief scientist for Security Research Labs, explained that they could not only locate cell-phone callers anywhere in the world, they could also listen in on their phone conversations. And if they couldn’t listen in real time, they could record the encrypted calls and texts for later decryption.

the ideal inductive approach, you will not have any prior beliefs about gender and its effects. In Strauss and Corbin’s famous description, “The researcher begins with an area of study and allows the theory to emerge from the data

As time goes on, I get more and more convinced that the right method in investment is to put fairly large sums into enterprises which one thinks one knows something about and in the management of which one thoroughly believes.” Forget what the economy is doing; just find well-managed companies, buy some shares, and don’t try to be too clever. And if that approach sounds familiar, it’s most famously associated with Warren Buffett, the world’s richest investor—and a man who loves to quote John Maynard Keynes.

Take a moment and surf over to Panopticlick.com. This is a site built by the Electronic Frontier Foundation that will determine just how common or unique your browser configuration is compared to others, based on what’s running on your PC or mobile device’s operating system and the plug-ins you may have installed.

for example the rule set called leetspeak—a system for replacing letters with numbers, as in “k3v1n m17n1ck.

Doing so showed that there was another variable that was a strong predictor of a person’s securing an entry in Wikipedia: the proportion of immigrants in your county of birth. The greater the percentage of foreign-born residents in an area, the higher the proportion of children born there who go on to notable success. (Take that, Donald Trump!) If two places have similar urban and college populations, the one with more immigrants will produce more prominent Americans. What explains this? A lot of it seems to be directly attributable to the children of immigrants. I did an exhaustive search of the biographies of the hundred most famous white baby boomers, according to the Massachusetts Institute of Technology’s Pantheon project, which is also working with Wikipedia data. Most of these were entertainers. At least thirteen had foreign-born mothers, including Oliver Stone, Sandra Bullock, and Julianne Moore. This rate is more than three times higher than the national average during this period. (Many had fathers who were immigrants, including Steve Jobs and John Belushi, but this data was more difficult to compare to national averages, since information on fathers is not always included on birth certificates.)

The concept of “confirmation bias”—the tendency of people to favor information, true or not, that confirms their preexisting beliefs—was introduced in the 1960s by Peter Wason, a British psychologist. Wason did a famous series of experiments that explored how people give lesser weight to data that contradicts what they think is true. (As if we needed more proof that what’s hidden can make us draw the wrong conclusions.)

He wondered whether the designers of the phone had performed clinical studies on snoozers in order to decide on the nine-minute interval. Why not eight minutes, or ten? The makers of the phone were famously particular about design. This had to have been data-driven.

But if you want to become famous, the worst possible thing to do is what we did: to pursue mathematics.

Otto captured this sacred sixth sense, at once subject and object, in a famous Latin sound bite: the sacred is the mysterium tremendum et fascinans, that is, the mystical (mysterium) as both fucking scary (tremendum) and utterly fascinating (fascinans).80 (page 9) With the sacred viewed within this gripping, emotionally charged sense, it is hardly surprising that these topics are too disturbing to be studied either by religious scholarship or by science. The presence of real siddhis, real psychic effects lurking in the dark boundaries between mind and matter, are so frightening and disorienting that defense mechanisms immediately snap into place to protect our psyches from these disturbing thoughts. We become blind to personal psychic episodes and to the supportive scientific evidence, we conveniently forget mind-shattering synchronicities, and if the intensity of the mysterium tremendum becomes too hot, we angrily deny any interest in the topic while backing away and vigorously making the sign of the cross. Within science this sort of behavior is understandable; science doesn’t like what it can’t explain because it makes scientists feel stupid. But the same resistance is also endemic in comparative religion scholarship, which is supposed to be the discipline that studies the sacred. As Kripal says, scholars of religion “simply ignore … or brush their data aside as ‘primitive,’ ‘mistaken,’ and so on. Now the dismissing word in vogue is ‘anecdotal’ ” (pp. 17–18).80 One reason for this odd state of affairs is that real psi and real siddhis powerfully refute Descartes’s dualism, the very idea that led to the split between science, which deals with matter, and the humanities, which deal with mind. This distinction has carved up the world so successfully that when phenomena appear that harshly illuminate the artificial nature of the split, the resulting glare, says Kripal, “can only violate and offend our present order of knowledge and possibility” (page 24).80 From this analysis, Kripal arrives at his central argument: Psychic phenomena may be thought of as symbols that indicate “the irruption [a bursting in] of meaning in the physical world via the radical collapse of the subject-object structure itself. They are not simply physical events. They are also meaning events” (page 25).80 In other words, where objective and subjective meet, the fabric of reality itself blurs. This is a place that is not quite physical, and not quite mental, but a limbo that somehow contains and creates both.

This part of the analysis, like any collection of human opinion, was sure to include old-fashioned prejudice and ignorance. It tended to protect the famous schools at the top of the list, because they were the ones people knew about. And it made it harder for up-and-comers.

About 30 percent of founding CEOs in the billion-dollar group had not worked for anyone other than themselves before. Of those who had, about 60 percent had worked at companies with very well-known brands, like Google, Microsoft, Amazon, Goldman Sachs, or McKinsey. Those “tier-one companies” are famous for their rigorous hiring processes and their tendency to employ the best. Another 28 percent worked at “tier-two companies,” which I define as large and well-known companies that were less sought-after by top talent. Only 14 percent of founders of billion-dollar companies had worked solely at companies that were not well-known brand names.

He skitters through the schoolyard like a traitor to childhood. He learns the shibboleths—the famous refrains from countless sitcoms, the hooks of pernicious little radio tunes, the bios of fifteen-year-old sexpot starlets he’s supposed to be slayed by. But at night, his dreams fill not with playground battles or the day’s take-down gossip but with visions of tight, lovely code doing more with less—bits of data passing from memory to register to accumulator and back in a dance so beautiful he can’t begin to tell his friends. They wouldn’t know how to see what he put in front of their eyes.

She is more phamous than she is famous.

Do not call attention to yourself with silly gestures. Do not believe that the joy of everyone in your proximity depends on you. Do not fear that one of them might be bored, in pain, or yearning for a list of famous local architects that you must volubly supply. Do not disgorge personal data to invoke an aura of mutual trust. Do not ask anyone their dearest wish or what they would like their last meal to be. Do not try too hard. Do not riff.

Old people vote. You know who votes in the swing states where this election will be fought? Really old people. Instead of high-profile videos with Cardi B (no disrespect to Cardi, who famously once threatened to dog-walk the egregious Tomi Lahren), maybe focus on registering and reaching more of those old-fart voters in counties in swing states. If your celebrity and music-industry friends want to flood social media with GOTV messages, let them. It makes them feel important and it’s the cheapest outsourcing you can get. Just don’t build your models on the idea that you’re going to spike young voter turnout beyond 20 percent. The problem with chasing the youth vote is threefold: First, they’re unlikely to be registered. You have to devote a lot of work to going out, grabbing them, registering them, educating them, and motivating them to go out and vote. If they were established but less active voters, you’d have voter history and other data to work with. There are lower-effort, lower-cost ways to make this work. Second, they’re not conditioned to vote; that November morning is much more likely to involve regret at not finishing a paper than missing a vote. Third, and finally, a meaningful fraction of the national youth vote overall is located in California. Its gigantic population skews the number, and since the Golden State’s Electoral College outcome is never in doubt, it doesn’t matter. What’s our motto, kids? “The Electoral College is the only game in town.” This year, the Democrats have been racing to win the Free Shit election with young voters by promising to make college “free” (a word that makes any economic conservative lower their glasses, put down the brandy snifter, and arch an eyebrow) and to forgive $1.53 trillion gazillion dollars of student loan debt. Set aside that the rising price of college is what happens to everything subsidized or guaranteed by the government.17 Set aside that those subsidies cause college costs to wildly exceed the rate of inflation across the board, and that it sucks to have $200k in student loan debt for your degree in Intersectional Yodeling. Set aside that the college loan system is run by predatory asswipes. The big miss here is a massive policy disconnect—a student-loan jubilee would be a massive subsidy to white, upper-middle-class people in their mid-thirties to late forties. I’m not saying Democrats shouldn’t try to appeal to young voters on some level, but I want them to have a realistic expectation about just how hard it is to move those numbers in sufficient volume in the key Electoral College states. When I asked one of the smartest electoral modeling brains in the business about this issue, he flooded me with an inbox of spreadsheets and data points. But the key answer he gave me was this: “The EC states in play are mostly old as fuck. If your models assume young voter magic, you’re gonna have a bad day.