AI World 1 · GenAI Foundations · Stage 1

Right Tool

Pick the AWS AI service each requirement needs, and know why not the others.

AI service choice
Managed AI services
Bedrock vs SageMaker AI
Traditional ML vs foundation models

Domain: AI and machine learning
World: AI World 1: GenAI Foundations (Associate)
Game type: Solution board: Drop services into each row's slots, then run records through them.
Time: About 15 minutes on a first attempt (estimated)
Articles: Amazon Bedrock or SageMaker AI: the question that decides
Which AWS AI service for which request: read the input, then the output
Exam guides: AIF-C01Task 1.1: Explain basic AI concepts and terminologies; Task 1.2: Identify practical use cases for AI; Task 2.3: Describe AWS infrastructure and technologies for building GenAI applications
MLA-C02Skill 2.1.3: Compare and select appropriate ML models, generative AI (GenAI) models, algorithms, and solution templates to meet business needs (for example, interpretability, domain-specific performance, latency); Skill 2.1.4: Evaluate tradeoffs between custom solutions, managed services, pre-trained models, and FMs to meet business needs; Skill 2.1.8: Apply AWS AI services to solve specific business problems (for example, Amazon Textract, Amazon Rekognition, Amazon Comprehend, Amazon Transcribe)
AIP-C01Skill 1.3.2: Create data processing workflows to handle complex data types including text, image, audio, and tabular data with specialized processing requirements for FM consumption (for example, by using Amazon Bedrock multimodal models, SageMaker Processing, AWS Transcribe); Skill 1.3.4: Enhance input data quality to improve FM response quality and consistency (for example, by using Amazon Bedrock to reformat text, Amazon Comprehend to extract entities, Lambda functions to normalize data)