When two doctoral candidates and an associate professor from the University of Kentucky presented a paper at last year’s British Machine Vision Conference, their work might have seemed destined for respectable academic obscurity. But a year on, the product of their research — an algorithm that estimates where the horizon line should be in a photograph — has found some unlikely takers. It has been used by a government defence agency to estimate where someone was standing when they took a picture, and by consumer photo services to correct for mistakes in users’ snaps. And for every 10,000 automated uses apps make of their algorithm, the academics pocket around $8. This example — from an app store for machine-learning called Algorithmia — is part of an explosion of interest in crowd-sourced algorithms. The technology industry has been promising a machine-learning revolution that will end up making all software smarter. The pieces are starting to fall into place to make that a reality.<...

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