Google is announcing that the Gemini API and Google AI Studio now both offer the ability to ground models using Google Search, which will improve the accuracy and reliability of Gemini’s responses.
By grounding the responses with Google Search results, responses can have fewer hallucinations, more up-to-date information, and richer information. Grounded responses also include links to the sources they are using.
“By providing supporting links, grounding brings transparency to AI applications, making them more trustworthy and encouraging users to click on the underlying sources to find out more,” Google wrote in a blog post.
This new capability supports dynamic retrieval, meaning that Gemini will assess if grounding is necessary, as not all queries need the extra assistant and it does add extra cost and latency. It generates a prediction score for every prompt, which is a measure of how beneficial grounding would be, and developers can adjust the prediction score threshold to what works best for their application.
Currently, grounding only supports text prompts and does not support multimodal prompts, like text-and-image or text-and-audio. It is available in all of the languages Gemini currently supports.
Google’s documentation on grounding provides instructions on how to configure Gemini models to use this new capability.