Exam AWS Certified AI Practitioner AIF-C01 topic 1 question 33 discussion

SageMaker JumpStart provides a catalog of pre-trained foundation models that can be quickly deployed It allows one-click deployment of FMs directly into your VPC through SageMaker endpoints Supports popular foundation models like Hugging Face models, AI21 Labs, Cohere, and others Enables quick deployment and consumption within your AWS infrastructure Models are deployed as SageMaker endpoints within your VPC for secure access Provides both pre-trained models and the ability to fine-tune them

B is the correct answer.

SageMaker endpoints is the correct answer

Endpoints will allow direct communication between VPC and Sagemaker

SageMaker Endpoints es el servicio fundamental que proporciona la capacidad de consumir un modelo (incluyendo FMs) de forma segura dentro de tu VPC. JumpStart es una excelente característica que te ayuda a crear esos Endpoints de FMs de manera más ágil. Dado que la pregunta abarca tanto el despliegue como el consumo dentro de la VPC, el Endpoint es la respuesta más abarcadora y técnicamente precisa para la funcionalidad clave de consumo y red.

Models deployed through SageMaker can be configured to run within your VPC, ensuring data privacy and network isolation.

Answer : Jumpstart SageMaker endpoints are part of the solution, but they don’t offer ready-to-deploy FMs on their own.

It allows deployment and consumption of foundation models within a VPC, meeting both the “quickly deploy” and “within the team’s VPC” requirements.

JumpStart itself is the platform for finding and accessing the models, but the deployment and consumption within the VPC happens through SageMaker endpoints. So correct answer is D

JumpStart is a tool that simplifies the process of preparing and deploying models, while Endpoints are the final destination for the deployed models, making them accessible for predictions. JumpStart can be thought of as a shortcut to deploying models, while Endpoints are the infrastructure that supports the actual model serving.

B. Amazon SageMaker JumpStart Explanation: • Amazon SageMaker JumpStart enables AI teams to quickly deploy and consume foundation models (FMs) within their own VPC. • It provides pre-trained foundation models from AWS and third-party providers, making it easy to fine-tune and integrate them into applications. • VPC Integration: Ensures that models are deployed securely within the team’s AWS environment.

Amazon SageMaker endpoints are a managed service feature that allows you to deploy models (including foundation models) for real-time inference. By hosting your model on an endpoint, you can make it accessible within your Virtual Private Cloud (VPC) and integrate it into your applications quickly. This approach provides a secure, scalable, and managed way to deploy and consume models across different teams. B. Amazon SageMaker JumpStart: Provides quick access to pre-trained models and sample solutions, but you ultimately deploy those models via SageMaker endpoints to consume them in your VPC.

Amazon SageMaker endpoints allow AI development teams to deploy and consume foundation models (FMs) within their Amazon VPC for secure, low-latency inference.

Amazon SageMaker JumpStart: Amazon SageMaker JumpStart helps developers quickly deploy and consume pre-trained models, including foundation models (FMs), within their environment. It provides a collection of ready-to-use models, workflows, and deployment solutions, allowing teams to get started quickly without having to build everything from scratch. It supports various ML use cases, making it an ideal choice for quickly deploying an FM in a VPC.

Amazon SageMaker JumpStart helps to deploy pre-trained Open-sourced models quickly.

The correct answer is B: Amazon SageMaker JumpStart. Here's why: Amazon SageMaker JumpStart is specifically designed to help teams quickly deploy and use foundation models (FMs) with the following benefits: Provides pre-trained models that can be deployed with just a few clicks Allows deployment within your VPC for secure access Includes popular foundation models from various providers Offers fine-tuning capabilities for customization Handles the infrastructure management automatically Amazon SageMaker endpoints - While these are used to deploy models, SageMaker JumpStart provides a more complete solution specifically for foundation models with built-in deployment capabilities

I lean towards Sagemaker Endpoints . to my knowledge Jumpstart will help you select/deploy the model, but to actually use it/consume it in your Prod/dev environment/VPC you need the Endpoint