Your Conversational AI Glossary
Here you will find in-depth explanations of all things related to Conversational AI.
A
AI Receptionist
An AI receptionist answers calls, greets callers, and handles inquiries using conversational artificial intelligence.
Algorithm
An algorithm is a set of rules an AI uses to solve problems or perform tasks.
AI Agent
An AI agent is software that autonomously performs tasks or conversations using artificial intelligence algorithms.
Artificial General Intelligence (AGI)
Artificial General Intelligence (AGI) refers to AI with human-like reasoning, learning, and problem-solving across domains.
Agentic AI
Agentic AI refers to autonomous systems capable of setting goals, making decisions, and executing tasks independently.
C
Call Routing
Smartly directs incoming calls to the right agent or department using real-time intent recognition and context.
Cognitive Computing
Cognitive computing mimics human thinking, like pattern recognition and learning, often used as a softer term for AI.
Conversational AI
Conversational AI enables computers to understand and respond to human language through speech or text.
D
Deep Learning
Deep learning is an AI method that mimics the brain to learn from unstructured data autonomously.
G
Generative AI
Deep learning is an AI method that mimics the brain to learn from unstructured data Generative AI uses machine learning to create original content like text, images, video, and code.
Gibberlink
Gibberlink connects conversations across devices, enabling AI to remember users and personalize every interaction.
I
IVR (Interactive Voice Response)
IVR (Interactive Voice Response) lets callers interact with a phone system using voice or keypad inputs.
L
LLM (Large Language Model)
An LLM (Large Language Model) is an AI trained to understand and generate human-like language.
M
Machine Learning (ML)
Machine learning (ML) enables computers to learn from data and make predictions without explicit programming.
Model Context Protocol (MCP)
Model Context Protocol (MCP) allows AI models to share memory, context, and tasks across applications.
N
Natural Language Processing (NLP)
NLP (Natural Language Processing) enables computers to understand, interpret, and respond to human language.
R
Reinforcement Learning
A machine learning approach where agents learn optimal behaviors through rewards and punishments from interactions with their environment
S
Speech-to-Text (STT)
Speech-to-text converts spoken language into written text using automatic speech recognition technology.
Supervised Learning
A type of machine learning where models are trained on labeled datasets to make predictions or classifications.
T
Text-to-Speech (TTS)
TTS (Text-to-Speech) technology converts written text into spoken audio using synthetic or AI-generated voices.
Transformer
A deep learning model architecture that has revolutionized natural language processing tasks through mechanisms like self-attention
U
Unsupervised Learning:
A machine learning technique that identifies patterns in unlabeled data without predefined categories or outcomes.
V
Voice Bot
A voice bot is an AI-powered system that interacts with users through spoken language.
Virtual Receptionist
A virtual receptionist answers calls, handles inquiries, and provides support remotely using software or live agents.
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