On September 20, at an event at Amazon’s Spheres, Amazon senior vice president for devices and services Dave Limp unveiled dozens of new device products and features. Later that day, Alexa head scientist Rohit Prasad went behind the scenes, explaining the scientific advances underlying Alexa’s newest features and capabilities.
A portrait of Rohit Prasad, vice president and head scientist, Alexa AI. He is wearing a black shirt and is photographed against a blue background.
Rohit Prasad, vice president and head scientist, Alexa AI

Alexa research and development falls into five major categories, Prasad explained. The first is competence, learning new skills and improving performance on existing ones. The next is context awareness, using information about the state of the world and about customers’ past interactions with Alexa to decide how best to handle a particular request. The third is expanding Alexa’s knowledge of facts and events, and the fourth is enabling more natural interaction with the Alexa voice service. "Being true to our promise to our customer that Alexa gets better every day,” Prasad said, the fifth category is self-learning, or automating the process whereby Alexa learns from experience.

"Most Alexa AI research is driven by machine-learning techniques that leverage large-scale AWS computing power and rich, heterogeneous data sets," explained Prasad. And here's how Alexa researchers are applying those techniques to these five research areas.