Connecting an AI system to live data sources—APIs, current news feeds, weather services, or real-time databases—lets it answer questions about what's happening now rather than what it learned during training. This is essential when accuracy depends on information that changes daily.
Grounding is the process of connecting an AI model to verified, up-to-date external sources such as web search results, documents, or databases so that its responses are anchored in current facts rather than relying solely on training data.
For everyday users, understanding grounding explains why AI with web access is more reliable for time-sensitive questions, and knowing when a model is grounded versus ungrounded helps you decide how much to trust the output before acting on it.
Peri can explain this concept, give practical examples, help you decide whether it applies to your situation, or recommend a journey if appropriate.
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