312-41 practice question 14 of 35

An enterprise is considering deploying an AI solution that will be used across multiple business domains to support various knowledge and…

An enterprise is considering deploying an AI solution that will be used across multiple business domains to support various knowledge and language-based tasks. Instead of developing separate AI models for each domain, the solution will be based on a common core capability, with domain- specific adjustments made where necessary. As the AI Portfolio Owner, your role is to ensure that this approach aligns with the company’s broader AI strategy and long-term investment priorities. You must assess the correct classification for this AI model to support future scalability and integration across the organization’s diverse functions. Which AI model classification best fits this strategy?

Answer options

A: Foundation Models Correct answer

B: Generative AI

C: Machine Learning

D: Large Language Models

Correct Answer:

A. Foundation Models

Explanation

The strategy of building a single, large-scale "common core capability" that can be adapted or fine-tuned for a wide variety of downstream tasks across different business domains is the definition of a Foundation Model. This approach promotes scalability, reusability, and avoids the cost of developing numerous specialized models from scratch. The enterprise's plan to use a central model with "domain-specific adjustments" directly maps to the concept of foundation models as a platform for building diverse AI applications.

Why Incorrect

B. Generative AI: This describes a capability (creating new content) and is too broad; the core of the strategy is the reusable architecture, not just the output.
C. Machine Learning: This is the entire field of study and is far too general to describe this specific architectural and strategic approach.
D. Large Language Models: This is a specific type of foundation model. "Foundation Model" is the correct, broader classification for the overall strategy.

References

1. Bommasani, R., et al. (2021). On the Opportunities and Risks of Foundation Models. Stanford University Institute for Human-Centered Artificial Intelligence (HAI). arXiv:2108.07258. Section 1.1, page 5, defines foundation models as "models trained on broad data at scale that can be adapted to a wide range of downstream tasks," which is precisely the strategy described.

2. National Institute of Standards and Technology (NIST). (2023, January). Artificial Intelligence Risk Management Framework (AI RMF 1.0). (NIST AI 100-1). Page 8 discusses foundation models as a key type of AI technology, noting their characteristic of being adaptable to many applications. https://doi.org/10.6028/NIST.AI.100-1

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