Google brings grounding with search to Gemini in AI Studio and API

Google LLC today announced it’s rolling out “grounding” for its artificial intelligence Gemini models using Google Search, which will enable developers to get more accurate and up-to-date responses aided by search results.

The new updates are available for AI Studio and the Gemini API. They permit the model to provide not just more accurate responses, but also returns from sources as in-line supporting links and suggestions that point users to search results within the response.

By grounding the model on search results, developers can bring in fresh data from search results to correct issues that might arise from out-of-date training data. When a user prompts an AI conversationally with a question, it replies with its best knowledge, but training can only answer with information that it has up to a certain point.

The response could have material that’s months old and therefore less accurate and less desirable. When a user makes a query with grounding turned on, Google said, the service uses its search engine to find up-to-date and comprehensive information relevant to the query and then sends it to the model.

Using search to ground AI responses will also allow the model to reply with more context and generate better results. As a result, the information will be richer and filled with better resources than just the model alone. With the addition of links to potential search resources, users will also have a chance to do additional research as well.

Grounding data based on Google Search can also help ensure that AI applications provide users with more factual information. According to the company, this can also reduce hallucinations, when an AI model’s response contains false or misleading information presented confidently.

Using the application programming interface, developers set a configuration that will determine when grounding is more or less likely to be beneficial for a query. In this setting, a value is assigned to every prompt between 0 and 1 that predicts if a prompt will benefit from grounding and the developer can set a threshold to activate grounding. A higher resulting number means that grounding will be more helpful. The default threshold is 0.7. Google suggested that developers experiment to see what setting best fits their application.

Google said this configuration exists because Grounding with Search will cause slower responses from Gemini models. Users may notice this slowdown in apps and it could make their experience feel worse. However, for those prompts that would benefit, the slower response would probably be negligible.

There is also the question of additional costs for using the new update. Grounding is available to test for free in Google AI Studio. In the API, developers can access the tool with the paid tier for $35 per 1,000 grounded queries.

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