If a computer can understand what a human means when they communicate, we can create all manner of applications of practical value from chatbots and conversational agents to systems that can read what we write in our documents and emails without losing meaning and context.
To gain that understanding, machines need to be able to understand and generate parts of speech, extract and understand entities, determine meanings of words, and use much more complicated processing activities to connect together concepts, phrases, concepts, and grammar into the larger picture of intent and meaning.
Development of more intelligent conversational systems goes back decades, with the ELIZA chatbot first developed in 1966 as an illustration of the possibilities of machine-mediated conversation.
Nowadays, users are more familiar with voice assistants such as Alexa, Google Assistant, Apple Siri, etc.
There’s no doubt that much of the work of AI researchers is going into improving the ways that machines can understand and generate human language and thus reinforce the power of those applications that leverage the conversational pattern of AI.