Google is bringing artificial intelligence to a whole new set of devices, including Android Wear 2.0 smartwatches and the Raspberry Pi board, later this year.
Google is bringing artificial intelligence to a whole new set of devices, including Android Wear 2.0 smartwatches and the Raspberry Pi board, later this year.
These devices don’t require a set of powerful CPUs and GPUs to carry out machine-learning tasks. Google researchers are instead trying to lighten the hardware load to carry out basic A. I. tasks, as exhibited by last week’s release of the Android Wear 2.0 operating system for wearables.
Google has added basic A. I. features to smartwatches with Android Wear 2.0, and those features can work within the limited memory and CPU constraints of wearables.
Android Wear 2.0 has a “smart reply” feature, which provides basic responses to conversations. It works much the way predictive dictionaries do, but it can auto-reply to messages based on the context of the conversation.
Google uses a new way to analyze data on the fly without bogging down a smartwatch. In conventional machine-learning models, a lot of data needs to be classified and labeled to provide accurate answers. Instead, Android Wear 2.0 uses a “semi-supervised” learning technique to provide approximate answers.
“We’re quite surprised and excited about how well it works even on Android wearable devices with very limited computation and memory resources,” Sujith Ravi, staff research scientist at Google said in a blog entry .
For example, the skimmed down machine-learning model can classify a few words — based on sentiment and other clues — and create an answer.
