AWS Certified AI Practitioner (AIF-C01) — Question 295

A company is using supervised learning to train an AI model on a small labeled dataset that is specific to a target task.

Which step of the foundation model (FM) lifecycle does this describe?

Answer options

• A. Fine-tuning
• B. Data selection
• C. Pre-training
• D. Evaluation

Correct answer: A

Explanation

Fine-tuning is the process of taking a pre-trained foundation model and training it further on a smaller, task-specific labeled dataset using supervised learning to adapt it to a particular application. Pre-training involves training a model from scratch on a massive unlabeled dataset, while data selection and evaluation refer to choosing training data and assessing model performance, respectively.