Simple as they may look, distribution centres are sophisticated structures. The machinery that moves stuff around is constantly evolving. Their playing field-sized floors have to be exceptionally level, as small unevenness could cause the high fork-lift trucks they use to lean unacceptably at the top. Years of competition have made their structure as spare and economical as can be. Architects such as Chetwoods have to reconcile all this with the wishes of users (who might want something tailored to their needs) and of investors, who will want a structure to be adaptable to future users.It is tempting to say that these buildings make the internet visible, except that their visibility is strictly limited. Sometimes they get into the news when reporters, posing as warehouse workers, bring news of working conditions inside. You can get a glimmer on Google, for example from employee reviews of Primark’s warehouse, which sits like an acropolis on a raised earthwork in Northamptonshire: “they’re treating a people like nothing,” says one in imperfect English; “they beautiful lied on induction how much they cares about worker, don’t believe them.” The buildings, however, remain notably blank, giving almost no clue of their busy inner lives.
Some users and owners are dismissive of press inquiries to a degree unusual in big, public relations-conscious companies. Tesco refused a request to see inside their Dirft base, which was possibly not surprising, but also to answer simple questions, such as: what are its dimensions?
For the writer Carolyn Steel, whose book Hungry City: How Food Shapes Our Livesexamines the relationship of society to food, this secrecy is the antithesis of the more public processes by which food once progressed from field to market to kitchen to plate. “The exchange of food used to bring people together,” she says. “Now the process is designed to exclude the human”. But distribution centres manifest the world we have chosen and had chosen for us, in return for efficiency and convenience, in which a product appears in the home by ever more inscrutable magic.
Their scale and growth are a consequence of the fact that all that physicality and volume that the virtual world displaces has to go somewhere. It’s welcome that architects and developers should try to make something of them and to mitigate their impact with woods, ponds and indeed coloured bands. But, short of a dramatic restructuring of the economic, technical and social basis of the modern world, these uncompromising building types will only become more essential to our lives. The contrast between what was previously thought of as natural and urban landscape will only become more stark.
In early 1999, during the halftime of a University of Washington basketball game, a time capsule from 1927 was opened. Among the contents of this portal to the past were some yellowing newspapers, a Mercury dime, a student handbook, and a building permit. The crowd promptly erupted into boos. One student declared the items “dumb.”
Such disappointment in time capsules seems to run endemic, suggests William E. Jarvis in his book Time Capsules: A Cultural History. A headline from The Onion, he notes, sums it up: “Newly unearthed time capsule just full of useless old crap.” Time capsules, after all, exude a kind of pathos: They show us that the future was not quite as advanced as we thought it would be, nor did it come as quickly. The past, meanwhile, turns out to not be as radically distinct as we thought.
In his book Predicting the Future, Nicholas Rescher writes that “we incline to view the future through a telescope, as it were, thereby magnifying and bringing nearer what we can manage to see.” So too do we view the past through the other end of the telescope, making things look farther away than they actually were, or losing sight of some things altogether.
These observations apply neatly to technology. We don’t have the personal flying cars we predicted we would. Coal, notes the historian David Edgerton in his book The Shock of the Old, was a bigger source of power at the dawn of the 21st century than in sooty 1900; steam was more significant in 1900 than 1800.
But when it comes to culture we tend to believe not that the future will be very different than the present day, but that it will be roughly the same. Try to imagine yourself at some future date. Where do you imagine you will be living? What will you be wearing? What music will you love?
Chances are, that person resembles you now. As the psychologist George Lowenstein and colleagues have argued, in a phenomenon they termed “projection bias,”1 people “tend to exaggerate the degree to which their future tastes will resemble their current tastes.”
In one experimental example, people were asked how much they would pay to see their favorite band now perform in 10 years; others were asked how much they would pay now to see their favorite band from 10 years ago. “Participants,” the authors reported, “substantially overpaid for a future opportunity to indulge a current preference.” They called it the “end of history illusion”; people believed they had reached some “watershed moment” in which they had become their authentic self.2 Francis Fukuyama’s 1989 essay, “The End of History?” made a similar argument for Western liberal democracy as a kind of endpoint of societal evolution.
This over- and under-predicting is embedded into how we conceive of the future. “Futurology is almost always wrong,” the historian Judith Flanders suggested to me, “because it rarely takes into account behavioral changes.” And, she says, we look at the wrong things: “Transport to work, rather than the shape of work; technology itself, rather than how our behavior is changed by the very changes that technology brings.” It turns out that predicting who we will be is harder than predicting what we will be able to do.
Entrepreneurs in Silicon Valley this year set themselves an audacious new goal: creating a brain-reading device that would allow people to effortlessly send texts with their thoughts.
In April, Elon Musk announced a secretive new brain-interface company called Neuralink. Days later, Facebook CEO Mark Zuckerberg declared that “direct brain interfaces [are] going to, eventually, let you communicate only with your mind.” The company says it has 60 engineers working on the problem.
It’s an ambitious quest—and there are reasons to think it won’t happen anytime soon. But for at least one small, orange-beaked bird, the zebra finch, the dream just became a lot closer to reality.
That’s thanks to some nifty work by Timothy Gentner and his students at the University of California, San Diego, who built a brain-to-tweet interface that figures out the song a finch is going to sing a fraction of a second before it does so.
“We decode realistic synthetic birdsong directly from neural activity,” the scientists announced in a new report published on the website bioRxiv. The team, which includes Argentinian birdsong expert Ezequiel Arneodo, calls the system the first prototype of “a decoder of complex, natural communication signals from neural activity.” A similar approach could fuel advances towards a human thought-to-text interface, the researchers say.
Police in the UK are starting to use futuristic technology that allows them to predict where and when crime will happen, and deploy officers to prevent it, research has revealed. “Predictive crime mapping” may sound like the plot of a far-fetched film, but it is already widely in use across the US and Kent Police is leading the technological charge in the UK.
A report on big data’s use in policing published by the Royal United Services Institute for Defence and Security Studies (RUSI) said British forces already have access to huge amounts of data but lack the capability to use it.
Alexander Babuta, who carried out the research, said predictive crime mapping tools had existed for more than a decade but are only being used by a fraction of British forces. “The software itself is actually quite simple – using crime type, crime location and date and time – and then based on past crime data it generates a hotspot map identifying areas where crime is most likely to happen,” he told The Independent…
I can look into your eyes and see straight to your heart.
It may sound like a sappy sentiment from a Hallmark card. Essentially though, that’s what researchers at Google did in applying artificial intelligence to predict something deadly serious: the likelihood that a patient will suffer a heart attack or stroke. The researchers made these determinations by examining images of the patient’s retina.
Google, which is presenting its findings Monday in Nature Biomedical Engineering, an online medical journal, says that such a method is as accurate as predicting cardiovascular disease through more invasive measures that involve sticking a needle in a patient’s arm.
AN ARTIFICIAL intelligence system can predict how a scene will unfold and dream up a vision of the immediate future.
Given a still image, the deep learning algorithm generates a mini video showing what could happen next. If it starts with a picture of a train station, it might imagine the train pulling away from the platform, for example. Or an image of a beach could inspire it to animate the motion of lapping waves.
Teaching AI to anticipate the future can help it comprehend the present. To understand what someone is doing when they’re preparing a meal, we might imagine that they will next eat it, something which is tricky for an AI to grasp. Such a system could also let an AI assistant recognise when someone is about to fall, or help a self-driving car foresee an accident.
“Any robot that operates in our world needs to have some basic ability to predict the future,” says Carl Vondrick at the Massachusetts Institute of Technology, part of the team that created the new system. “For example, if you’re about to sit down, you don’t want a robot to pull the chair out from underneath you.
To teach the AI to make better videos, the team used an approach called adversarial networks. One network generates the videos, and the other judges whether they look real or fake. The two get locked in competition: the video generator tries to make videos that best fool the other network, while the other network hones its ability to distinguish the generated videos from real ones.
Big data is predicting things about your life almost every minute of your day — whether you’re aware of it or not.
Amazon is predicting what else you might like to buy every time you shop. Netflix is predicting what you might want to watch. Google is predicting how you will respond to your emails. And Match.com and other dating sites are even trying to predict who you might fall in love with.
These predictions have become so ubiquitous that we don’t always even notice them any more. But data analysts are working on predicting much more important outcomes than the next show you’ll binge watch, with some very exciting results…
For years, fashion industry has had previous data and intuition at its disposal to predict customer demands which is now becoming quite irrelevant considering the fast-changing fashion trends and the tough competition in the market. More so, with more and more people getting brand conscious, it is becoming tougher for aspiring fashion designers to make a place on the mannequins. But they need not worry; Big Data is here to save the budding talent!
Unbelievable but true, Big Data is becoming an important part of one of the most intuition-based and unpredictable industry. In a world where clothes become outdated with the release of a new movie or the latest fashion week, even biggies like Burberry and Ralph Lauren have resorted to Big Data analysis. The runway at the fashion week, the latest edition of Cosmopolitan — are all losing their charm; designers these days release photos of their exclusive collections on Social Media (Facebook, Twitter, Instagram, Pinterest) which helps them know the trends and people’s response much before the curtain-raiser. Sentiment analysis through collection of the responses (likes, shares, comments, re-tweets) helps the industry to analyse every aspect of consumers demand— from the most loved colour to the most acceptable fit…