Different models of conversational intelligence tradeoff performance, developer effort and controllability. Which model are you using?
There are many choices of models for your conversational AI, and understanding these choices can help you make the decision between using a pre-existing framework or implementing your own. We will describe nine approaches; however, before we begin, let’s have a look at the foundational concepts of behavior and intelligence referred to throughout this article.
A simple way of describing agent behavior is a mapping from stimulus to response. Consider the following human and machine behaviors:
Voice-enabled products are reducing friction and maximizing utility all while being more conscious of end-user data privacy concerns.
After a decade that produced two generations of voice assistants, the technological enablers that will power the next wave of conversational AI are evident now. Speech recognition accuracy has improved, while taking the concerns…
An overview of the past decade in conversational AI
In order to identify the technical enablers that are driving the next generation of conversational AI, it is important to understand how they connect to key trends in previous generations. Below we offer an overview of the past and present of conversational AI.
Voice-based interaction systems can trace their roots back to the days of telephony. Interactive voice response (IVR) based customer service offered over the phone allowed companies to reduce their operating costs.