Progress on improving skill discovery
Most recently, Amazon introduced
Alexa Conversations, a Deep Learning approach that allows developers to more effectively improve skill discovery with less effort, fewer lines of code, and less training data. While it is still in “preview”, Alexa Conversations has already
generated considerable excitement among developers who build skills for the smart speaker.
Essentially, Alexa Conversations aims to establish a more natural and fluid interaction between Alexa and its users within a single skill. In future releases, the software is expected to bring multiple skills into a single conversation. It also claims to be able to handle ambiguous references, such as, “Are there any Italian restaurants nearby?” (near where?), as well as context preservation when transitioning from one skill to another, such as remembering the location of a certain movie theater when suggesting nearby restaurants.
At Amazon’s re:MARS AI and ML conference in June,
Rohit Prasad, VP and head scientist at Alexa, mentioned that
Alexa Conversations’ machine learning capabilities can help it predict a customer’s true intention and goal from the direction of the dialogue, thus proactively enabling flow across multiple skills during conversation. If these promises are met, the command-query interaction with Alexa will surely begin to feel more like a natural human interaction.