Since pioneering the in-flight Internet business, Gogo has dominated, commanding about 80 percent of the market. And as often happens with near monopolies, Gogo has become a name people love to hate. ... For years, customer perceptions that Gogo is basically Comcast at 35,000 feet didn’t hurt the company’s bottom line. Users were literally a captive audience, and if they didn’t like the service, too bad, read a book. But for the first time since that Louis C.K. rant, Gogo has some serious competition. At least two companies—ViaSat and Global Eagle Entertainment (GEE)—are encroaching on its airspace, winning business by offering faster, cheaper connections that use satellites instead of cell towers. ... It’s spent almost $1 billion developing onboard equipment and a network of transmission towers across North America. Back then, travelers in business class who needed to work used laptops or occasionally BlackBerrys or Palm Treos. ... Today, the company provides service on more than 2,000 commercial aircraft. It employs almost 900 people and had revenue of $409 million in 2014, up almost 25 percent from the previous year. ... What Gogo does in the sky is, indeed, different from what wireless companies do on terra firma. It uses an air-to-ground system that functions similarly to traditional cell service, but its radio towers point up, not down. Gogo’s towers are anywhere from 50 to 200 feet tall and can be located in rather remote locations, such as atop peaks in the Rocky Mountains or deep in the Alaskan tundra.
Matt Ginsberg’s training is in astrophysics. He got his Ph.D. from Oxford when he was 24 years old. His doctoral advisor there was the famed mathematical physicist Roger Penrose, and he recalls rubbing elbows with the academic rock stars Stephen Hawking and the late Richard Feynman. He created an artificial intelligence crossword puzzle solver called Dr. Fill and a computer bridge world champion called GIB. ... Unsurprisingly, there’s pretty heavy math involved to make this real-time sports predictor work. For one element of the system’s calculations, Ginsberg sent me a pdf with eight dense pages of physics diagrams and systems of equations and notes on derivations. It uses something called the Levenberg-Marquardt algorithm. It requires Jacobians and the taking of partial derivatives and the solving of quartics, and code efficient enough to calculate it all up to the split second. If predicting the future were easy, I suppose everybody would do it. ... One thing this project can’t predict, however, is its own future. Its uses are, so far, largely speculative, and cashing in on a minor superpower might not be easy. Even gamblers who bet during play would struggle to make much money from a half-second heads-up that a shot is going in. But Ginsberg’s system would find a natural place in the long line of sports technologies that have been used for a singular end — TV.
The device, which costs about $40,000, is called a spectrum analyzer. And for years Dooley, a consultant and self-appointed expert who left college after a year, has been measuring and recording wireless data traffic—the billions of transmissions that travel back and forth from smartphones and laptops to cell towers, routers, and other Internet connections. If you’re checking Facebook on your iPhone and Dooley is nearby, his machine will see it and light up. And if hordes of people are posting pictures to Instagram and streaming Netflix videos all around him, the display on Dooley’s machine will turn bright red. Dooley takes the readings to track which parts of the electromagnetic spectrum—the frequencies that carry everything from radio signals to X-rays—are degrading from overuse. He likes to think of himself as a “21st-century version of a land surveyor.” ... What Dooley’s machine is telling him now is this: Wi-Fi is headed for a collapse. The preferred Internet connection for most users is quickly becoming overcrowded, he argues, and could soon be overwhelmed. ... According to Cisco, the amount of data transmitted via Wi-Fi is projected to nearly triple in the next four years. The problem, says Dooley, is that the signals from all our wired devices are increasingly beginning to bump into one another, causing performance to suffer. ... a growing chorus of critics say that Globalstar’s warnings about a Wi-Fi apocalypse are completely unfounded—and that its plan, rather than fixing spectrum congestion, would actually make the situation much worse.
Guinness brewer William S. Gosset’s work is responsible for inspiring the concept of statistical significance, industrial quality control, efficient design of experiments and, not least of all, consistently great tasting beer. ... Because he used a pseudonym, his name isn’t even familiar to most people who frequently use his most famous discovery. Gosset is the “student” of the Student’s T-Test, a method for interpreting what can be extrapolated from a small sample of data. ... Born in 1876 in Canterbury, England, Gosset entered a world of enormous privilege. His father was a Colonel in the Royal Engineers, and though he intended to follow in his footsteps, he was unable to due to bad eyesight. Instead, Gosset attended the prestigious Winchester College, and then Oxford, where he studied mathematics and natural sciences. Soon after graduating from Oxford, in 1899, Gosset joined the Guinness brewery in Dublin, Ireland, as an experimental brewer.
Netflix’s video algorithms team had developed a number of quality levels, or recipes, as they’re called in the world of video encoding. Each video file on Netflix’s servers was being prepared with these same recipes to make multiple versions necessary to serve users at different speeds. ... Netflix’s service has been dynamically delivering these versions based on a consumer’s bandwidth needs, which is why the quality of a stream occasionally shifts in the middle of a binge-watching session. But across its entire catalog of movies and TV shows, the company has been using the same rules — which didn’t really make sense. ... they decided that each title should get its own set of rules. This allows the company to stream visually simple videos like “My Little Pony” in a 1080p resolution with a bitrate of just 1.5 Mbps. In other words: Even someone with a very slow broadband or mobile internet connection can watch the animated show in full HD quality under the new approach. Previously, the same consumer would have just been able to watch the show with a resolution of 720*480, and still used more data.
The untold tale of Target Canada’s difficult birth, tough life and brutal death ... Fisher, 38 years old at the time, was regarded as a wunderkind who had quickly risen through the ranks at Target’s American command post in Minneapolis, from a lowly business analyst to leader of a team of 400 people across multiple divisions. Launching the Target brand in a new country was his biggest task to date. The news he received from his group that February afternoon should have been worrying, but if he was unnerved, Fisher didn’t let on. He listened patiently as two people in the room strongly expressed reticence about opening stores on the existing timetable. Their concern was that with severe supply chain problems and stores facing the prospect of patchy or empty shelves, Target would blow its first date with Canadian consumers. Still, neither one outright advocated that the company push back its plans. “Nobody wanted to be the one to say, ‘This is a disaster,’” says a former employee. But by highlighting the risks of opening now, the senior employees’ hope was that Fisher would tell his boss back in Minneapolis, Target CEO Gregg Steinhafel, that they needed more time. ... Nobody disagreed with the negative assessment—everyone was well aware of Target’s operational problems—but there was still a strong sense of optimism among the leaders, many of whom were U.S. expats. The mentality, according to one former employee, was, “If there’s any team in retail that can turn this thing around, it’s us.” ... Roughly two years from that date, Target Canada filed for creditor protection, marking the end of its first international foray and one of the most confounding sagas in Canadian corporate history. The debacle cost the parent company billions of dollars, sullied its reputation and put roughly 17,600 people out of work.
Plank has the affect and intensity of a head coach--direct eye contact, military analogies, the air of someone you do not want to disappoint. "Winning is a part of our culture--it's who we are," he says in his lofty office overlooking the harbor. (The only artwork behind his desk: a giant UA logo, its letters stacked to evoke arms raised in victory.) "And culture is formed on habits." Perhaps the most important guardrail, and the company's official mission, is seeking to "make all athletes better." It has long equaled thinking about clothes as high-performance gear, but recently it's taken on a big new meaning. ... Over the past two years, Under Armour has spent close to $1 billion buying and investing in three leading makers of activity- and diet-tracking mobile apps. By doing so, the company has amassed the world's largest digital health-and-fitness community, with 150 million users. Plank envisions all of those users, and their metrics, as a big data engine to drive everything from product development to merchandising to marketing. Many observers, though, balked at the $710 million cost of the acquisitions ... the high-stakes bet on Connected Fitness will be slow to pay off. Under Armour recently increased its projections for the next two years, estimating that it would nearly double net revenue by 2018, to $7.5 billion (up from a previous estimate of $6.8 billion). Only $200 million--a paltry 2.7 percent--will come from Connected Fitness. ... "If I'm right," he says, Connected Fitness "becomes a force multiplier that takes us from shirts-and-shoes company to true technology company. If I'm wrong, it costs us some money--we have $710 million on the table."
Until recently the military junta had imposed artificial caps on access to smartphones and SIM cards. Many of the farmers we spoke with had never owned a smartphone before. The villages were often without running water or electricity, but they buzzed with newly minted cell towers and strong 3G signals. For them, everything networked was new. ... Almost all of the farmers we spoke with were Facebook users. None had heard of Twitter. How they used Facebook was not dissimilar to how many of us in the West see and think of Twitter: as a source of news, a place where you can follow your interests. The majority, however, didn’t see the social platform as a place to be particularly social or to connect with and stay up to date on comings and goings within their villages. ... What follows are a series of diary entries and notes culled from our interviews. The interview teams were composed of three or four people: a translator, a photographer, a notetaker, and sometimes a facilitator. ... Everyone is data sensitive he says and reiterates: Facebook. Nobody needs a special app for their interests. Just search for your interest on Facebook. Facebook is the Internet. ... Everyone installs apps using Zapya, an app-sharing app. Makes a local network. Everyone nearby connects to it. Allows groups to send data—apps, videos, music—back and forth without using bandwidth. ... there is no incumbent electric giant monopolizing rural areas to fight against solar, there is no incumbent bank which will lobby against bitcoin, there are no expectations about how a computer should work, how a digital book should feel. There is only hunger and curiosity. ... They don’t have email addresses and so often don’t know their logins. If they get logged out they have someone—often the village Facebook guru—make them a new account. “Friends” on Facebook are friends only because the application calls them friends in the interface.
He bounces from smart locks, to smart lights, to a smart shower, to smart shoe insoles. It almost backfires when a Samsung representative demonstrating a smart refrigerator reaches out and flips his badge back over, asking, “What are you, press?” But his name doesn’t mean anything to her, and Pichai just casts an amused sideways glance and dives in with questions. “So, what can I ask the fridge?” he wants to know. Various versions of this same scene play out again and again. ... With $74.5 billion in annual revenue last year, Google is by far the largest (and only profitable) business under Alphabet. Indeed, Google has seven different products that more than a billion people use: Search, Gmail, YouTube, Android, Chrome, Maps, and its app and media vending machine, the Google Play Store. ... Google is sprinting to attract its “next billion” users. For the most part, these are people in the developing world; people who will go online, for the very first time, using one of Google’s Android-powered handsets. Which puts Google in the position of being seen as both a corporate NSA and modern East India Company. ... Android was, very literally, made for this moment. Its entire point is to be customized, reconfigured, and personalized for a world full of people across a range of sizes, shapes, configurations, and price points. Sure, signs for the $550 Nexus abound, but you can also score a cheap Android phone in Delhi, like a Lava Atom X, for less than $40 — and that’s without a contract. It will, Pichai thinks, change the status quo not just in India, but the entire world.
Conventional wisdom says that globalization has stalled. But although the global goods trade has flattened and cross-border capital flows have declined sharply since 2008, globalization is not heading into reverse. Rather, it is entering a new phase defined by soaring flows of data and information. ... Remarkably, digital flows—which were practically nonexistent just 15 years ago—now exert a larger impact on GDP growth than the centuries-old trade in goods ... although this shift makes it possible for companies to reach international markets with less capital-intensive business models, it poses new risks and policy challenges as well. ... The world is more connected than ever, but the nature of its connections has changed in a fundamental way. The amount of cross-border bandwidth that is used has grown 45 times larger since 2005. It is projected to increase by an additional nine times over the next five years as flows of information, searches, communication, video, transactions, and intracompany traffic continue to surge. In addition to transmitting valuable streams of information and ideas in their own right, data flows enable the movement of goods, services, finance, and people. Virtually every type of cross-border transaction now has a digital component.
Easy access to capital has allowed the company to bid aggressively on content for its service. This year Netflix will spend $5 billion, nearly three times what HBO spends, on content, which includes what it licenses ... dozens of original shows (more than 600 hours of original programming are planned for this year) often receive as much critical acclaim and popular buzz as anything available on cable. ... But the assembled executives also had reason to worry. Just because Netflix had essentially created this new world of internet TV was no guarantee that it could continue to dominate it. Hulu, a streaming service jointly owned by 21st Century Fox, Disney and NBC Universal, had become more assertive in licensing and developing shows, vying with Netflix for deals. And there was other competition as well: small companies like Vimeo and giants like Amazon, an aggressive buyer of original series. Even the networks, which long considered Netflix an ally, had begun to fight back by developing their own streaming apps. Last fall, Time Warner hinted that it was considering withholding its shows from Netflix and other streaming services for a longer period. ... At the moment, Netflix has a negative cash flow of almost $1 billion; it regularly needs to go to the debt market to replenish its coffers. Its $6.8 billion in revenue last year pales in comparison to the $28 billion or so at media giants like Time Warner and 21st Century Fox. And for all the original shows Netflix has underwritten, it remains dependent on the very networks that fear its potential to destroy their longtime business model in the way that internet competitors undermined the newspaper and music industries. Now that so many entertainment companies see it as an existential threat, the question is whether Netflix can continue to thrive in the new TV universe that it has brought into being.
Let us say it plainly: Monsanto is almost surely the most vilified company on the planet. To its diehard critics it embodies all that is wrong with big, industrial agriculture—the corporatization of farming, the decline of smallholders, the excessive use of chemicals, a lack of transparency, and, of course, the big one: the entry of genetically modified organisms into our food supply. The tri-letter acronym GMO has become a four-letter word to millions of people, from earnest middle-schoolers to purist Whole Foods shoppers. ... The United Nations’ Food and Agriculture Organization estimates that we must double the current level of food production to adequately feed a population predicted to hit 9.7 billion by 2050—and we’ll have to do it on less land (much of it scarce of water), using fewer resources. ... Historically, Monsanto has tried to increase farm yields through advancements in seed technology alone. Grant calls this “hubris”: “Twenty years ago,” he says, “we thought biotech was going to be the panacea.” In the past half-decade the company has begun to look beyond seed for answers. ... Breeding better seed has contributed to a more than 1% annual increase in corn yields, experts say. Biologists, for instance, have created corn plants that can be clustered closer together, meaning there can be more stalks per acre. Still, that yearly growth rate would leave the U.S. average below 200 bushels by the end of the decade—far from Hula’s corn bonanza and nowhere near enough to feed the planet. ... Combined, those seeds now fill some 400 million acres around the globe. That’s a fraction of the nearly 4 billion acres of land the UN estimates is being cultivated. Climate Corp.’s chief technology officer Mark Young doubts that that Monsanto could ever get to a billion-acre footprint just by being a seed company, “but as a decision-based company, it seems to have a really good shot.” Monsanto, for example, doesn’t sell grape seeds, but it could some day advise grape growers on how to increase their yields.
Farms, then, are becoming more like factories: tightly controlled operations for turning out reliable products, immune as far as possible from the vagaries of nature. Thanks to better understanding of DNA, the plants and animals raised on a farm are also tightly controlled. Precise genetic manipulation, known as “genome editing”, makes it possible to change a crop or stock animal’s genome down to the level of a single genetic “letter”. This technology, it is hoped, will be more acceptable to consumers than the shifting of whole genes between species that underpinned early genetic engineering, because it simply imitates the process of mutation on which crop breeding has always depended, but in a far more controllable way. ... Understanding a crop’s DNA sequence also means that breeding itself can be made more precise. You do not need to grow a plant to maturity to find out whether it will have the characteristics you want. A quick look at its genome beforehand will tell you. ... Such technological changes, in hardware, software and “liveware”, are reaching beyond field, orchard and byre. Fish farming will also get a boost from them. And indoor horticulture, already the most controlled and precise type of agriculture, is about to become yet more so. ... In the short run, these improvements will boost farmers’ profits, by cutting costs and increasing yields, and should also benefit consumers (meaning everyone who eats food) in the form of lower prices. In the longer run, though, they may help provide the answer to an increasingly urgent question: how can the world be fed in future without putting irreparable strain on the Earth’s soils and oceans?
The US polling industry has been suffering a crisis of insight over the past decade or so; its methods have become increasingly bad at telling which way America is leaning. ... The classic pollster’s technique known as random digit dialing, in which firms robo-dial phone after phone, is failing, because an ever-dwindling number of people have landlines. ... whereas a survey in the 1970s or 1980s might have achieved a 70 percent response rate, by 2012 that number had fallen to 5.5 percent, and in 2016 it’s headed toward an infinitesimal 0.9 percent. And finally, the demographics of participants are narrowing: An elderly white woman is 21 times more likely to answer a phone poll than a young Hispanic male. So polling samples are often inherently misrepresentative. ... Today’s polling landscape appears so fraught that Gallup, long the industry leader, opted out of presidential horse-race polls this year; the reputational risk of being wrong was simply too high. Civis, on the other hand, promises a paradigm that could rescue American politics from confusion. ... Today, campaigns realize they have to look elsewhere for their intelligence, which has caused a major change in how the political industry functions. In the past, an entire campaign’s data and infrastructure would go poof after Election Day. Now Civis and similar firms are building institutional memory with permanent information storehouses that track America’s 220 million–odd voters across their adult lives, noting everything from magazine subscriptions and student loans to voting history, marital status, Facebook ID, and Twitter handle. Power and clients flow to the firms that can build and maintain the best databases of people’s behavior over time.
This problem has a name: the paradox of automation. It applies in a wide variety of contexts, from the operators of nuclear power stations to the crew of cruise ships, from the simple fact that we can no longer remember phone numbers because we have them all stored in our mobile phones, to the way we now struggle with mental arithmetic because we are surrounded by electronic calculators. The better the automatic systems, the more out-of-practice human operators will be, and the more extreme the situations they will have to face. ... The paradox of automation, then, has three strands to it. First, automatic systems accommodate incompetence by being easy to operate and by automatically correcting mistakes. Because of this, an inexpert operator can function for a long time before his lack of skill becomes apparent – his incompetence is a hidden weakness that can persist almost indefinitely. Second, even if operators are expert, automatic systems erode their skills by removing the need for practice. Third, automatic systems tend to fail either in unusual situations or in ways that produce unusual situations, requiring a particularly skilful response. A more capable and reliable automatic system makes the situation worse. ... The rarer the exception gets, as with fly-by-wire, the less gracefully we are likely to deal with it. We assume that the computer is always right, and when someone says the computer made a mistake, we assume they are wrong or lying. ... For all the power and the genuine usefulness of data, perhaps we have not yet acknowledged how imperfectly a tidy database maps on to a messy world. We fail to see that a computer that is a hundred times more accurate than a human, and a million times faster, will make 10,000 times as many mistakes. ... If you occasionally need human skill at short notice to navigate a hugely messy situation, it may make sense to artificially create smaller messes, just to keep people on their toes.
Mass, who is 64, has become the most widely recognized critic of weather forecasting in the United States — and specifically the National Oceanic and Atmospheric Administration, which manages the National Weather Service and its underling agencies, including the National Centers for Environmental Prediction, where the nation’s weather models are run. Mass argues that these models are significantly flawed in comparison with commercial and European alternatives. American forecasting also does poorly at data assimilation, the process of integrating information about atmospheric conditions into modeling programs; in the meantime, a lack of available computing power precludes the use of more advanced systems already operating at places like the European Center for Medium-Range Weather Forecasts, based in Reading, England. And there are persistent management challenges, perhaps best represented by the legions of NOAA scientists whose innovations remain stranded in research labs and out of the hands of the National Weather Service operational forecasters who make the day-to-day predictions in 122 regional offices around the country. ... accuracy is everything, often the difference between life and death, given that extreme weather ... Industries like shipping, energy, agriculture and utilities lose money when predictions fail. Even slightly more precise wind-speed projections would help airlines greatly reduce fuel costs. ... the Weather Service interface was so primitive — the protocol was originally designed for the telegraph — it could only accommodate uppercase type.
Next year it will be 60 years since people first witnessed the majesty of a satellite being launched into orbit: Sputnik 1, hurled into the night sky in Kazakhstan early on October 5th 1957. ... Just 15 years separated the launch of the first satellite and the return of the last man from the moon, years in which anything seemed possible. But having won the space race, America saw no benefit in carrying on. Instead it developed a space shuttle meant to make getting to orbit cheap, reliable and routine. More than 100 shuttle flights between 1981 to 2011 went some way to realising the last of those goals, despite two terrible accidents. The first two were never met. Getting into space remained a risky and hideously expensive proposition, taken up only by governments and communications companies, each for their own reasons. ... New rockets, though, are not the only exciting development. The expense of getting into space during the 1980s and 1990s led some manufacturers to start shrinking the satellites used for some sorts of mission, creating “smallsats”. Since then the amount a given size of satellite can do has been boosted by developments in computing and electronics. This has opened up both new ways of doing old jobs and completely novel opportunities. ... No single technology ties together this splendid gaggle of ambitions. But there is a common technological approach that goes a long way to explaining it; that of Silicon Valley. Even if for now most of the money being spent in space remains with old government programmes and incumbent telecom providers, space travel is moving from the world of government procurement and aerospace engineering giants to the world of venture-capital-funded startups and business plans that rely on ever cheaper services provided to ever more customers.
Wu believes Opendoor can buy and sell homes, in quantity, by employing the type of data analysis that has powered so many Silicon Valley companies and by targeting the broad middle of the market. It deals in single-family homes built after 1960, priced between $125,000 and $500,000. It has no interest in distressed properties, which require too much work, or in luxury properties, which are harder to value. ... Of course, buying up houses to make a market is capital-intensive, and the risks are great. Opendoor has raised $110 million in equity from Khosla Ventures, GGV Capital and Access Industries, among others, most recently at a valuation of $580 million earlier this year. And it has also raised more than $400 million in debt to buy the homes. To succeed, it has to price the homes it buys accurately, without seeing them, and it has to sell them quickly to minimize the costs of carrying them. ... Opendoor is a big, bold play in a market with $1.4 trillion in annual transaction volume that’s been largely undisturbed for decades. ... the model has yet to be tested by a recession or a market crash, which can catch even the smartest players by surprise. Wu says he modeled the business through the 2008 subprime crisis to understand the risk.
Yet the mystery of the mechanism is only partly solved. No one knows who made it, how many others like it were made, or where it was going when the ship carrying it sank. ... What if other objects like the Antikythera Mechanism have already been discovered and forgotten? There may well be documented evidence of such finds somewhere in the world, in the vast archives of human research, scholarly and otherwise, but simply no way to search for them. Until now. ... Scholars have long wrestled with “undiscovered public knowledge,” a problem that occurs when researchers arrive at conclusions independently from one another, creating fragments of understanding that are “logically related but never retrieved, brought together, [or] interpreted,” as Don Swanson wrote in an influential 1986 essay introducing the concept. ... In other words, on top of everything we don’t know, there’s everything we don’t know that we already know. ... Discovery in the online realm is powered by a mix of human curiosity and algorithmic inquiry, a dynamic that is reflected in the earliest language of the internet. The web was built to be explored not just by people, but by machines. As humans surf the web, they’re aided by algorithms doing the work beneath the surface, sequenced to monitor and rank an ever-swelling current of information for pluckable treasures. The search engine’s cultural status has evolved with the dramatic expansion of the web. ... Using machines to find meaning in vast sets of data has been one of the great promises of the computing age since long before the internet was built.
- Also: Quartz - Inside the secret meeting where Apple revealed the state of its AI research < 5min
- Also: The Library Quarterly - Undiscovered Public Knowledge > 15min
- Also: AAAI - Undiscovered Public Knowledge: a Ten-Year Update 5-15min
- Also: Wired - Inside OpenAI, Elon Musk’s Wild Plan to Set Artificial Intelligence Free 5-15min
Despite years of economic growth, popular discontent at widespread corruption has grown stronger. A series of scandals about everything from shoddy housing to out-of-date vaccines has led to public cynicism about companies and the government’s ability to enforce rules. Social-credit scoring aims to change that by cracking down on the corrupt officials and companies that plague Chinese life. And it aims to keep a closer track on public opinion. In a society with few outlets for free expression, big data might paradoxically help make institutions more accountable. ... But it could also vastly increase snooping and social control. In other countries there have been many scare stories about Big Data leading to Big Brother. Most have proven false. But China is different. It is a one-party state, with few checks on its power, a tradition of social control and, in President Xi Jinping, a leader even more prone to authoritarianism than his immediate predecessors. The extent of social-credit scoring will depend on what the government intends, whether the technology works and how the party responds to public concerns. ... China treats personal information differently from the West. In democracies, laws limit what companies may do with it and the extent to which governments can get their hands on it. Such protections are imperfect everywhere. But in China they do not exist. The national-security law and the new cyber-security law give the government unrestricted access to almost all personal data.
For decades, poultry had been volatile in a frustratingly predictable way: When times started getting good, companies flooded the market with chicken, causing prices to crash. ... At first the transformation puzzled industry watchers. Some speculated that a merger spree during the 1980s and 1990s was responsible—with fewer decision-makers in charge and fewer competitors, the remaining companies could more easily survey and predict the landscape. But Sanderson’s conference call suggested another source for the shift: Agri Stats, a private service that gathers data from poultry processors, produces confidential weekly reports, and disseminates them back to companies that pay for subscriptions. ... Many industries, such as health care and retail, make use of information-sharing services, but Agri Stats provides chicken producers with a rare level of detail, in uncommonly timely fashion. ... Agri Stats has for years maintained that its reports don’t violate antitrust laws, in part because the information provided is historical. A typical report doesn’t say how much a company plans to charge for a cut of meat, only what it charged last month or last week. ... In 2013, according to SEC filings, Eli Lilly purchased Agri Stats for an undisclosed sum and folded it into its farm animal drug division. ... Illegal collusion occurs when companies plan with one another to cut production ahead of time with the specific intent of raising prices.
The gift for talent-spotting is mysterious, highly prized and celebrated. We love to hear stories about the baseball coach who can spot the raw ability of an erratic young pitcher, the boss who sees potential in the guy in the post room, the director who picks a soloist out of the chorus line. Talent shows are a staple of the TV schedules. We like to believe that certain people – sometimes ourselves – can just sense when a person has something special. But there is another method of spotting talent which doesn’t rely on hunches. In place of intuition, it offers data and analysis. Rather than relying on the gut, it invites us to use our heads. It tends not to make for such romantic stories, but it is effective – which is why, despite our affection, the hunch is everywhere in retreat. ... The low level of the validity ceiling makes sense when you think about the web of interacting forces – individual ability, organisational culture, social and economic change, pure luck – involved in any success or failure. Weather forecasters using vast databases can say with confidence if it’s going to rain only a few days in advance. Predicting the outcome of human endeavour is even more complex – imagine if clouds had feelings – yet we desperately want to believe our hunches can tell us what will happen in a year or five years’ time.
Over the past 12 years, Lt. Megge has increased the speed limit on nearly 400 of Michigan’s roadways. Each time, he or one of his officers hears from community groups who complain that people already drive too fast. But as Megge and his colleagues explain, their intent is not to reduce congestion, bow to the reality that everyone drives too fast, or even strike a balance between safety concerns and drivers’ desire to arrive at their destinations faster. Quite the opposite, Lt. Megge advocates for raising speed limits because he believes it makes roads safer. ... This “nationally recognized method” of setting the speed limit as the 85th percentile speed is essentially traffic engineering 101. It’s also a bit perplexing to those unfamiliar with the concept. Shouldn’t everyone drive at or below the speed limit? And if a driver’s speed is dictated by the speed limit, how can you decide whether or not to change that limit based on the speed of traffic? ... The answer lies in realizing that the speed limit really is just a number on a sign, and it has very little influence on how fast people drive.
Here we have a basketball mystery: a player is widely regarded inside the N.B.A. as, at best, a replaceable cog in a machine driven by superstars. And yet every team he has ever played on has acquired some magical ability to win. ... The virus that infected professional baseball in the 1990s, the use of statistics to find new and better ways to value players and strategies, has found its way into every major sport. Not just basketball and football, but also soccer and cricket and rugby and, for all I know, snooker and darts — each one now supports a subculture of smart people who view it not just as a game to be played but as a problem to be solved. Outcomes that seem, after the fact, all but inevitable — of course LeBron James hit that buzzer beater, of course the Pittsburgh Steelers won the Super Bowl — are instead treated as a set of probabilities, even after the fact. The games are games of odds. Like professional card counters, the modern thinkers want to play the odds as efficiently as they can; but of course to play the odds efficiently they must first know the odds. Hence the new statistics, and the quest to acquire new data, and the intense interest in measuring the impact of every little thing a player does on his team’s chances of winning. In its spirit of inquiry, this subculture inside professional basketball is no different from the subculture inside baseball or football or darts. The difference in basketball is that it happens to be the sport that is most like life. ... the player who seems one step ahead of the analysts, helping the team in all sorts of subtle, hard-to-measure ways that appear to violate his own personal interests.
S.L. Benfica—Portugal's top football team and one of the best teams in the world—makes as much money from carefully nurturing, training, and selling players as actually playing football. Football teams have always sold and traded players, of course, but Sport Lisboa e Benfica has turned it into an art form: buying young talent; using advanced technology, data science, and training to improve their health and performance; and then selling them for tens of millions of pounds—sometimes as much as 10 or 20 times the original fee. ... All told, S.L. Benfica raised more than £270 million (€320m) from player transfers over the last six years. ... How much they eat and sleep, how fast they run, tire, and recover, their mental health—everything is ingested into a giant data lake. ... each player receives a personalised training regime where weaknesses are ironed out, strengths enhanced, and the chance of injury significantly reduced. ... Benfica uses a custom middleware layer that sanitises the output from each sensor into a single format ... The sanitised data is then ingested into a giant SQL data lake hosted on the team's own data centre.