Conversational AI

AI (Artificial Intelligence)

The simulation of human intelligence in machines designed to think, learn, and solve problems like a human.

Chatbot

An AI-driven software that simulates a conversation with users, either via text or voice, and is often used to provide customer service or assistance.

Natural Language Processing (NLP)

A branch of AI that focuses on enabling machines to understand, interpret, and generate human language.

Natural Language Understanding (NLU)

A subfield of NLP that focuses on machine comprehension of human language, such as recognizing intent and extracting entities from text.

Intent

The goal or purpose behind a user’s query or command in conversational AI, often identified through NLP.

Entity Recognition

The process of identifying and classifying important elements (such as dates, locations, or product names) from a user’s input in conversational AI.

Dialogue Management

The component of conversational AI systems responsible for managing the conversation flow, context, and determining the appropriate response.

Speech Recognition

The process of converting spoken language into text, allowing voice-based conversational AI systems to understand and respond to user commands.

Voice Assistant

An AI-based system that uses voice recognition and NLP to understand and execute spoken commands, examples include Alexa, Siri, and Google Assistant.

Machine Learning (ML)

A subset of AI focused on algorithms that enable machines to learn from and make predictions or decisions based on data.

Training Data

The data used to teach a conversational AI model to understand and respond to user inputs correctly, often containing examples of text or speech.

Reinforcement Learning

A type of machine learning where an agent learns by interacting with an environment and receiving feedback in the form of rewards or penalties.

Chatbot Framework

A set of tools, libraries, and APIs used to build and deploy chatbots or conversational AI systems, often providing templates and pre-built functionality.

Multimodal AI

AI systems capable of processing and responding to inputs across multiple modes, such as text, voice, and visual cues, for more complex interactions.

Contextual AI

AI that maintains context throughout a conversation, allowing it to recall previous interactions and provide more coherent and personalized responses.

Want to explore more? Stay tuned for new terms and updates!