Thanks to advances in speech recognition, artificial intelligence, neural networks, and processing power, we can tap into the capabilities of our machines simply by speaking paid googlecloud
, Alexa, Siri, Bixby, and Cortana. And with each passing month, conversational AI is becoming smarter and less constrained by specific use cases—which means not only that most households may soon trade in those myriad controllers for a voice assistant but also that those voice assistants will grow more human-like, intuitive, and useful.
The likelihood that so many applications will be quickly abandoned points to the improvements that still need to be made—which raises two obvious questions: How do these conversational technologies work? And how are they being made better?Conversation is second nature for humans, but conversational AI is extraordinarily difficult for machines. Why is that? Let’s deconstruct what happens when you participate in a conversation.
This is called response generation, and it’s influenced by the same contextual nuances we’ve seen before, such as the identity of the speaker and the situation in which the exchange occurs. A simple request like “Do you take American Express?” might be addressed with a simple “no.” That’s informative, but it’s not very useful. “No, but we take Visa” is a more natural human response.
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