Einstein Studio (Model Builder) allows organizations to connect and utilize external foundational models while fine-tuning them with company-specific data. This capability is particularly suited to businesses like Universal Containers (UC) that require customization of foundational models to better align with their unique data and use cases.
Option A: Adjusting model temperature is a parameter-level setting for controlling randomness in AI-generated responses but does not necessitate connecting to an external foundational model.
Option B: This is the correct answer because Einstein Studio supports fine-tuning external models with proprietary company data, enabling a tailored and more accurate AI solution for UC.
Option C: Changing frequency penalties is another parameter-level adjustment and does not require external foundational models or Einstein Studio.
[Reference:, "Using Einstein Studio to Connect Foundational Models | Salesforce Trailhead" ., , , , ]
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