These AI technologies leverage both machine learning and deep learning—different elements of AI, with some nuanced differences—to develop an increasingly granular knowledge base of questions and responses informed by user interactions.
Modern AI chatbots now use natural language understanding (NLU) to discern the meaning of open-ended user input, overcoming anything from typos to translation issues. Advanced AI tools then map that meaning to the specific “intent” the user wants the chatbot to act upon and use conversational AI to formulate an appropriate response. These AI technologies leverage both machine learning and deep learning—different elements of AI, with some nuanced differences—to develop an increasingly granular knowledge base of questions and responses informed by user interactions. This sophistication, drawing upon recent advancements in large language models (LLMs), has led to increased customer satisfaction and more versatile chatbot applications.