What is Grounding (AI)?
Connecting AI responses to verifiable facts and real-world data sources.
Definition
Grounding refers to techniques that anchor AI responses to factual, verifiable information rather than relying solely on training data. This includes citing sources, connecting to databases, and using RAG to reduce hallucinations.
Examples
Why It Matters
Grounded AI is more trustworthy. Look for tools that cite sources and connect to real data.
Related Terms
Common Questions
What does Grounding (AI) mean in simple terms?
Connecting AI responses to verifiable facts and real-world data sources.
Why is Grounding (AI) important for AI users?
Grounded AI is more trustworthy. Look for tools that cite sources and connect to real data.
How does Grounding (AI) relate to AI chatbots like ChatGPT?
Grounding (AI) is a fundamental concept in how AI assistants like ChatGPT, Claude, and Gemini work. For example: Perplexity citing web sources Understanding this helps you use AI tools more effectively.
Related Use Cases
AI Models Using This Concept
See Grounding (AI) in Action
Council lets you compare responses from multiple AI models side-by-side. Experience different approaches to the same prompt instantly.