Glossary

A branch of computer science focused on creating systems or machines that can perform tasks typically requiring human intelligence. These tasks include learning, reasoning, problem-solving, perception, and language understanding.

A software entity that can perform certain tasks independently and proactively without the need for human intervention. An AI agent can autonomously perceive its environment through sensors, processes information, and takes actions to achieve specific goals. 

They can range from simple automated systems to advanced entities capable of learning, adapting, and making decisions based on data.

It is the framework that defines the components and their interactions within an AI system, enabling it to perform tasks requiring human-like intelligence. This includes modules for data processing, learning algorithms, decision-making mechanisms, and communication interfaces.

A software platform that enables the creation, training, and deployment of AI agents.  These agents are designed to perform specific tasks autonomously or with minimal human intervention.

See More: AI agent builders

Though subject to debate, ASI is a hypothetical form of AI that surpasses human intelligence across all domains, including creativity, general wisdom, and problem-solving.

Explore: AI Agent Builders

Agentic AI refers to AI systems that ingest vast amounts of data from multiple data sources and third-party applications to independently analyze challenges, develop strategies and execute tasks. They are characterized by their ability to observe their environment, process information, and take actions to achieve specific goals or tasks. 

A type of AI that possesses the ability to understand, learn, and apply knowledge across a wide range of tasks at a level comparable to human intelligence. AGI systems are designed to perform any intellectual task that a human can do, rather than being limited to specific, pre-programmed tasks.

Assumptions made by an AI model about the data leading to unfair or prejudiced outcomes. Bias can arise from various sources, including biased training data, flawed algorithms, or human prejudices embedded in the system.

A large-scale AI language model developed by OpenAI that generates human-like text.

A computer program designed to simulate human conversation through text or voice interactions. Chatbots can respond to text or voice inputs, providing information, answering questions, or assisting with tasks. They use natural language processing (NLP) to understand and generate responses.

Related: Chatbot AI Agents

Conversational AI is a type of artificial intelligence (AI) that can simulate human conversation.  It combines several AI technologies to understand, process, and respond to human language in a way that feels interactive and intuitive.

Explore: Conversational AI agents

Deep learning is a subset of machine learning that uses multilayered neural networks, called deep neural networks, to simulate the complex decision-making power of the human brain.

AI systems that are designed to explain their decisions and actions in a way that humans can understand.  The goal of XAI is to make the inner workings of AI systems more interpretable to humans, enabling users to trust and effectively interact with AI. 

The process of taking a pre-trained AI model and making small adjustments to it using a specific dataset related to a particular task. 

Generative artificial intelligence (generative AI, GenAI, or GAI) is a subset of artificial intelligence that uses generative models to produce text, images, videos, or other forms of data.

Related: Use cases of GenAI