core concepts

Grounding

Techniques for connecting AI model outputs to verifiable, real-world information sources to reduce hallucinations. Grounding ensures model responses are anchored in factual data rather than relying solely on patterns learned during training.

In practice

A grounded AI assistant retrieves current stock prices from an API rather than guessing them from training data.

Hallucination
When an AI model generates confident but factually incorrect, fabricated, or nonsensical information. Hallucinations occur because language models produce statistically plausible text rather than verified facts, and they cannot distinguish between what they know and what they are generating.
RAG
Retrieval-Augmented Generation, a technique that enhances language model outputs by retrieving relevant information from external knowledge sources before generating a response. RAG reduces hallucinations and keeps responses current without retraining the model.
Retrieval
The process of finding and fetching relevant information from a knowledge base or document store to provide context for AI model responses. Retrieval systems use techniques like semantic search and keyword matching to find pertinent data.

In the index

Tools that mention Grounding

Google NotebookLMTrust 85

Matched on each tool’s own description and feature list, highest trust score first.

Briefings

Grounding

Tools that mention Grounding

Further reading