Mobile means that, for the first time, pretty much everyone on earth will have a camera, taking vastly more images than were ever taken on film (‘How many pictures?’). This feels like a profound change on a par with, say, the transistor radio making music ubiquitous.
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We should expect that every image ever taken can be searched or analyzed, and some kind of insight extracted, at massive scale. Every glossy magazine archive is now a structured data set, and so is every video feed. With that incentive (and that smarthome supply chain) far more images and video will be captured.[…]
Now, suppose you buy the last ten years’ issues of Elle Decoration on eBay and drop them into just the right neural networks, and then give that system a photo of your living room and ask which lamps it recommends? All those captioned photos, and the copy around them, are training data. And yet, if you don’t show the user an actual photo from that archive, just a recommendation based on it, you probably don’t need to pay the original print publisher itself anything at all. (Machine learning will be fruitful grounds for IP lawyers.) We don’t have this yet, but we know, pretty much, how we might do it. We have a roadmap to recognize some kind of preferences, automatically, at scale.
from Stowe Boyd http://www.stoweboyd.com/post/153682884087
