Could natural language models improve their ability to answer questions on the fly? That's what a team of Amazon researchers set out to answer in a study scheduled to be presented at the 2020 Association for the Advancement of Artificial Intelligence in New York. They posit a method for adapting models based on Google's Transformer architecture -- which is particularly good at learning long-range dependencies among input data (such as the semantic and syntactic relationships between individual words of a sentence) -- to address the problem of answer selection. The team says that in tests on a benchmark data set, their proposed model demonstrated a 10% absolute improvement in mean average precision (which measures the quality of a sorted list of answers according to the correctness of the ranking) over the previous state-of-the-art answer selection model, achieving an error rate reduction of 50%. The approach -- Transfer and Adapt, or TANDA -- was first proposed late last year but has since been refined.

Alexa somewhat recently gained what Amazon calls "name-free skill interaction," which enables it to parse intent from requests that don't explicitly name third-party voice apps. But as scientists at the Seattle company's Alexa AI research division note, it's more challenging than it seems on the surface -- the AI system that maps utterances to skills (dubbed "Shortlister") would ideally need to be retrained from scratch each time new skills are added to the Alexa Skills Store. Fortunately, they managed to devise a labor-saving alternative described in a new paper ("Continuous Learning for Large-scale Personalized Domain Classification") scheduled to be presented at the North American Chapter of the Association for Computational Linguistics in New Orleans. It entails "freezing" the settings of the AI model to add new components that accommodate new skills and training these new components only on data pertaining to them. An Amazon spokesperson told VentureBeat it's being implemented in production "on a limited basis" -- i.e., not for all of the roughly 90,000 available Alexa skills just yet.