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Best of the Web

The secrets of a great subway map

(Thinkstock)

(Thinkstock)

Our pick of the week from around the web, including the true threat of artificial intelligence, a chilling hacker experience, and a rude awakening in genetics.

The science of a great subway map
Eric Jaffe | Fast Company | 29 October 2013
Researchers at MIT find a way to determine how well subway users comprehend the system map at a single glance. And, apparently, Massimo Vignelli, who designed the schematised New York subway map of the 1970s, really did know what he was doing. Legible map design stresses visual clarity over geographical precision. Subway lines should be bold ribbons of colour running vertically or horizontally

Review: Tesla Motors Model S
Lee Hutchinson | Ars Technica | 28 October 2013
A rave review of the all-electric car. “As for the driving experience – well, you forget about all of the neat electronics and the touchscreen and the battery when you slip behind the wheel …The Model S doesn’t smell like oil, it doesn’t drink gasoline, and it doesn’t howl when you stomp on it. But even though it lacks a beating mechanical internal combustion heart, it absolutely, positively, most definitely does have a soul”.

The argument machine
Derek Powazek | 27 October 2013
Suppose you are an evil genius building a device for plunging rational, well-meaning people into furious arguments. What would your argument machine look like? Probably it would encourage people to pepper one another with assertions in public. It would also allow bystanders to repeat comments out of context. In fact: it would be Twitter.
 
Genetics: The rite of passage
David Dobbs | Slate | 27 October 2013
Rapid advances in genetics have been slow to produce practical applications. “Many thought sequencing the human genome would unlock the door and show us the genome’s machinery, with all the parts and controls conveniently marked. Instead, it showed us a genome that was mostly unmarked and ludicrously complicated – so complicated that even 13 years later, its workings remain mysterious”.

Amazon and the profitless business model
Eugene Wei | Remains of the Day | 26 October 2013
Why Amazon doesn’t report profits. Yet. “Amazon’s core business model does generate a profit with most every transaction at its current price level. The reason it isn’t showing a profit is because it’s undertaken a massive investment to support an even larger sales base … If I were an Amazon competitor, I’d regard Amazon’s current run of losses as a terrifying signal. Amazon is arming itself to take the contest to higher ground”.

I challenged hackers to investigate me
Adam Penenberg | Pando Daily | 26 October 2013
And they did. With terrifying success. Read and tremble. “They got into our checking and savings accounts, a corporate bond account, our credit card statements and online bills. They could, if they wanted to, have wiped us out financially … They breached my Facebook account, and ordered 100 plastic spiders from Amazon, then had them shipped to my home. My laptop shut down and demanded a four-digit code to gain re-entry”.

The threat of artificial intelligence
Gary Marcus | New Yorker | 24 October 2013
“For now, most of the machines that are good enough to play chess haven’t shown the slightest interest in acquiring resources. But the goals of machines could change as they get smarter. Once computers can effectively reprogram themselves, and successively improve themselves, the risks of machines outwitting humans in battles for resources and self-preservation cannot simply be dismissed.” 

Douglas Hofstadter: replicating the human mind
James Somers | Atlantic 23 | October 2013
Hofstadter shot to fame with Gödel, Escher, Bach in 1980, a book that “launched an entire generation of eager young students” into the study of artificial intelligence. He’s been working on AI ever since, but outside, and possibly far ahead of, the tech-driven mainstream. He seeks to model how the human brain thinks; not merely to write programmes that do particular things faster or better than humans.

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