For years, Swami Sivasubramanian’s wife has wanted to get a look at the bears that come out of the woods on summer nights to plunder the trash cans at their suburban Seattle home. So over the Christmas break, Sivasubramanian, the head of Amazon’s AI division, began rigging up a system to let her do just that.
So far he has designed a computer model that can train itself to identify bears—and ignore raccoons, dogs, and late-night joggers. He did it using an Amazon cloud service called SageMaker, a machine-learning product designed for app developers who know nothing about machine learning. Next, he’ll install Amazon’s new DeepLens wireless video camera on his garage. The $250 device, which will go on sale to the public in June, contains deep-learning software to put the model’s intelligence into action and send an alert to his wife’s cell phone whenever it thinks it sees an ursine visitor.
Sivasubramanian’s bear detector is not exactly a killer app for artificial intelligence, but its existence is a sign that the capabilities of machine learning are becoming far more accessible. For the past three years, Amazon, Google, and Microsoft have been folding features such as face recognition in online photos and language translation for speech into their respective cloud services—AWS, Google Cloud, and Azure. Now they are in a headlong rush to build on these basic capabilities to create AI-based platforms can be used by almost any type of company, regardless of its size and technical sophistication.
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