A product team wants to add summarization to its app using ready-made models, while a separate research group wants to build and train its own forecasting models on proprietary data. Which pairing of AWS services matches those needs?
Show answer and explanation
Answer: B
Bedrock provides managed API access to pre-trained foundation models and also offers customization options, which suits a product team that wants generative AI without building models. SageMaker AI is a broader platform for preparing data, training, tuning and hosting models the team controls, which suits a research group building forecasting models on proprietary data. The choice comes down to consuming existing models versus building your own. The two services are not interchangeable, and SageMaker typically asks for more ML expertise than Bedrock.
Why the other options are wrong
- A. SageMaker AI does far more than storage; it covers training, tuning and hosting of custom models.
- C. Bedrock serves foundation models for text and other modalities, so it is not limited to image classifiers.
- D. The services overlap somewhat but differ in purpose, so treating them as substitutes leads to poor fits.
Exam tip. Bedrock to consume foundation models; SageMaker AI to build and operate custom models.