They say AI trained on dog behavior could be useful for teaching robots
What can artificial intelligence learn from dogs? Quite a lot, say researchers from the University of Washington and Allen Institute for AI. They recently trained neural networks to interpret and predict the behavior of canines. Their results, they say, show that animals could provide a new source of training data for AI systems — including those used to control robots.
To train AI to think like a dog, the researchers first needed data. They collected this in the form of videos and motion information captured from a single dog, a Malamute named Kelp. A total of 380 short videos were taken from a GoPro camera mounted to the dog’s head, along with movement data from sensors on its legs and body. Essentially, Kelp was being recorded in the same way Hollywood uses motion capture to record actors playing CGI creations. But instead of Andy Serkis bringing Gollum to life, they were capturing a dog going about its daily life — walking, playing fetch, and going to the park.
With this information in hand, the researchers analyzed Kelp’s behavior using deep learning. This is an AI technique that can be used to sift patterns from data. In this case, that meant matching the motion data of Kelp’s limbs and the visual data from the GoPro with various doggy activities. The resulting neural network trained on this information could predict what a dog would do in certain situations. If it saw someone throwing a ball, for example, it would know that the reaction of a dog would be to turn and chase it.
Speaking to The Verge, the paper’s lead author, Kiana Ehsani, explained that the predictive capacity of their AI system was very accurate, but only in short bursts. In other words, if the video shows a set of stairs, then you can guess the dog is going to climb them. But beyond that, life is simply too varied to predict. “Whether or not the dog will see a toy or an object it wants to chase, who knows,” says Ehsani, a PhD student at the University of Washington.