Machine learning gives environmentalists something to tweet about

The team faced some unique challenges. They were starting with a small quantity of labelled data, the software would often pick up other noises like construction, cars and even doorbells, and some of the bird species had a variety of birdsongs or two would sing at the same time. To overcome these hurdles, they tested, verified and retrained the system many times over. As a result, they have learned things that would have otherwise remained locked up in thousands of hours of data. While it's still early days, already conservation groups are talking to Victor about how they can use these initial results to better target their efforts.