Smart doll fitted with AI chip can read your child’s emotions
Feeling sad? Soon your dolls will be able to tell. To demonstrate the power of a new chip that can run artificially intelligent algorithms, researchers have put it in a doll and programmed it to recognise emotions in facial images captured by a small camera.
The doll can recognise eight emotions in total, including surprise and happiness, all while running on a small battery and without doing any processing in the cloud. The total cost of putting the new chip together is just €115 – an indicator of how easy it is becoming to give devices basic AI abilities.
“In the near future, we will see a myriad of eyes everywhere that will not just be watching us, but trying to help us,” says project leader Oscar Deniz at the University of Castilla-La Mancha in Ciudad Real, Spain.
Recent advances in AI mean we already have algorithms that can recognise objects, lip-read, make basic decisions and more. It’s only a matter of time before these abilities make their way on to little cheap chips like this one, and then put into consumer devices.
“We will have wearable devices, toys, drones, small robots, and things we can’t even imagine yet that will all have basic artificial intelligence,” says Deniz.
One of the advantages of Deniz’s chip not needing the internet to function is privacy. Last year, a smart doll called My Friend Cayla attracted a lot of controversy because it couldn’t do its processing locally. To recognise what children were saying, it sent audio clips to the cloud and then worked out an appropriate response. “Can I tell you a secret,” a child might ask. “Sure go ahead,” the doll would reply.
Children could share intimate details about their lives with their new friend only for that conversation to be recorded and sent to a data centre. Clearly, that’s not how many parents want smart toys. Privacy advocates also raised concerns over the Hello Barbie doll, which used speech recognition to interact with children’s requests – but also passed the data to third-party servers for storage and processing.
At the moment, Deniz’s project is focused on processing data from a camera rather than a microphone, but many of the issues are the same.
Running computer vision algorithms locally is also incredibly important in many situations, says Massimiliano Versace at Boston University. A self-driving car moving at 120 kilometres per hour doesn’t have time to do all of its decision-making in the cloud because of a lack of bandwidth. So those decisions need to be made locally.
“Today we live in a world where devices are dumb. Tomorrow we will live in a world where devices can think,” says Versace. Moving away from dependence on the cloud is a vital step for AI, he says.
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