Using a Generative Model to Drive a Conversation to a Hardquarter Anostat

In this episode, we discussed the Alexa Prize Socialbot Grand Challenge and this year's winning submission, Alquist 4.0, with Petr Marek, a member of the winning team. Petr gave us an overview of their submission, the design choices that led to them winning the competition, including combining a hardcoded dialog tree and a neural generator model and extracting implicit personal information about users from their responses, and some outstanding challenges. Petr Marek is a PhD student at the Czech Technical University in Prague. More about the Alexa Prize challenges: https://developer.amazon.com/alexaprize Technical report on Alquist 4.0: https://arxiv.org/abs/2109.07968