Alexa’s ability to respond to customer requests is largely the result of machine learning models trained on annotated data. The models are fed sample texts ...

Many of today’s most useful AI systems are multilabel classifiers: they map input data into multiple categories at once. An object recognizer, for instance, ...

Earlier this month, Varun Sharma and Akshit Tyagi, two master’s students from the University of Massachusetts Amherst, began summer internships at Amazon, ...

Using machine learning to train information retrieval models — such as Internet search engines — is difficult because it requires so much manually annotated ...

This month, Amazon announced the 11 focus areas of the 2019 Amazon Research Awards, a program that provides up to $80,000 in funding and up to $20,000 in ...

Computerized question-answering systems usually take one of two approaches. Either they do a text search and try to infer the semantic relationships between ...

This year, at the Association for Computational Linguistics’ Workshop on Natural-Language Processing for Conversational AI, my colleagues and I won one of ...

Alexa currently has more than 90,000 skills, or abilities contributed by third-party developers — the Uber ride-sharing skill, the Jeopardy! trivia game ...

Neural networks are responsible for most recent advances in artificial intelligence, including many of Alexa’s latest capabilities. But neural networks tend ...

Alexa currently has more than 90,000 skills, or abilities contributed by third-party developers — the NPR skill, the Find My Phone skill, the Jeopardy! ...

A text-to-speech system, which converts written text into synthesized speech, is what allows Alexa to respond verbally to requests or commands. Through a ...

An automatic-speech-recognition system — such as Alexa’s — converts speech into text, and one of its key components is its language model. Given a sequence ...