Expand Your Knowledge of AI and Data Readiness

GenAI refers to a class of AI systems designed to generate new content, such as text, images, audio, video, and code, based on patterns learned from large datasets.

An advanced form of artificial intelligence that can act autonomously to plan, make decisions, and take actions toward achieving goals with minimal human intervention.

The process of teaching a generative AI model by exposing it to large volumes of data so it can learn patterns, language, and concepts. The data used during training is retained within the model’s internal structure, shaping how it responds. 

Additional information or structure that helps an AI system understand and use data effectively. It enables an Agent to understand what the data means and how to leverage it to generate a response.

Data that is properly prepared, structured, and enriched to be effectively used by AI systems. It is the foundation that enables reliable, scalable, and accurate AI applications.

A system that can autonomously perceive its environment, make decisions, and take actions to achieve specific goals. ChatD&B, Dun & Bradstreet’s conversational AI assistant to help users make faster, data-driven decisions, is considered an AI agent.

This is a Dun & Bradstreet term for D&B raw data made available to clients for use within their AI systems; generally for conversational GenAI tools like ChatD&B.

A Google-developed protocol that enables AI agents to communicate, coordinate, and collaborate with each other. It allows agents to exchange tasks, context, and capabilities in a standardized way, unlocking more dynamic and scalable multi-agent workflows.

Tools integrated into the ChatD&B system that serve a specific purpose but work together to provide responses to user queries. Data-centric tools are constructed from a limited set of data blocks and contain context which helps the AI system to understand the included data.

An open standard designed to enable AI systems (especially LLMs) to interact seamlessly with external tools, data sources, and services to fetch data, execute functions, and integrate with other systems.

A method where AI retrieves relevant information from an external knowledge source (e.g., a database, website, etc.), then generates a response based on that information.