A company uses Amazon SageMaker for its ML pipeline in a production environment. The company has large input data sizes up to 1 GB and processing times up to 1 hour. The company needs near real-time latency.Which SageMaker inference option meets these requirements?
Answer(s): C
Asynchronous inference is suitable for handling large input data and long processing times while still providing responses without blocking other requests. It allows for near real-time latency, whereas the other options are less suitable given the input size and processing time constraints.
HOTSPOT (Drag and Drop is not supported)A company is using data from multiple departments to build predictive models. Each department provides data in different formats and structures. The company must correctly identify each data type before the company can pre-process the data.Select the correct data format from the following list for each description. Select each data format one time or not at all.Hot Area:
Answer(s): A
Unlabeled data contains raw information without assigned categories, annotations, or target variables.Structured data follows a predefined schema with clearly defined fields and relationships. Tabular data is organized into rows and columns with consistent fields across records.
A company has deployed an ML model. The company wants to provide external customers with secure access to the model through the customers' own applications.Which solution will meet these requirements?
A secure API endpoint allows external customers to access the deployed ML model through their own applications while enforcing authentication, authorization, monitoring, and controlled access without exposing model credentials directly.
A company has a foundation model (FM) that was customized by using Amazon Bedrock to answer customer queries about products. The company wants to validate the model's responses to new types of queries. The company needs to upload a new dataset that Amazon Bedrock can use for validation.Which AWS service meets these requirements?
Amazon S3 is the most suitable AWS service for uploading and storing datasets used for validation purposes.It is highly scalable and integrated with Amazon Bedrock, allowing easy access to data for model validation.The other options do not provide the same level of integration or suitability for managing datasets in this context.
A company is building a generative AI tool. The company will use internal documents to customize a foundation model (FM).Which approach will meet this requirement?
Answer(s): B
Continued pre-training involves further training a foundation model (FM) on internal documents, allowing the model to better understand and generate content specific to the company's context and requirements. This approach customizes the FM using the company’s own data.
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