Why data is the new coal


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.
But there is a coda to the story: 69 years later, James Watt made a nice tweak to the Newcomen steam engine, adding a condenser to the design. That change, Lawrence said, “made the steam engine much more efficient, and that’s what triggered the industrial revolution”.
“If you look at all the areas where deep learning is successful, they’re all areas where there’s lots of data,” points out Lawrence. That’s great if you want to categorise images of cats, but less helpful if you want to use deep learning to diagnose rare illnesses. “It’s generally considered unethical to force people to become sick in order to acquire data.”


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