An anonymous reader shares a report on The Guardian: "Is data the new oil?" asked proponents of big data back in 2012 in Forbes magazine. By 2016, and the rise of big data's turbo-powered cousin deep learning, we had become more certain: "Data is the new oil," stated Fortune. Amazon's Neil Lawrence has a slightly different analogy: Data, he says, is coal. Not coal today, though, but coal in the early days of the 18th century, when Thomas Newcomen invented the steam engine. A Devonian ironmonger, Newcomen built his device to pump water out of the south west's prolific tin mines. The problem, as Lawrence told the Re-Work conference on Deep Learning in London, was that the pump was rather more useful to those who had a lot of coal than those who didn't: it was good, but not good enough to buy coal in to run it. That was so true that the first of Newcomen's steam engines wasn't built in a tin mine, but in coal works near Dudley. So why is data coal? The problem is similar: there are a lot of Newcomens in the world of deep learning. Startups like London's Magic Pony and SwiftKey are coming up with revolutionary new ways to train machines to do impressive feats of cognition, from reconstructing facial data from grainy images to learning the writing style of an individual user to better predict which word they are going to type in a sentence.
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