AI

Here's a comprehensive breakdown of AWS AI services:

1. Core AI/ML Services

• Amazon SageMaker

  • Full ML platform

  • Model development, training, deployment

  • Built-in algorithms

  • Notebooks and development environments

  • MLOps capabilities

1. AI Applications

• Vision:

  • Rekognition (image/video analysis)

  • Lookout for Vision (visual inspection)

• Language/Text:

  • Comprehend (NLP)

  • Translate

  • Textract (document processing)

  • Transcribe (speech-to-text)

  • Kendra (intelligent search)

• Speech:

  • Polly (text-to-speech)

  • Lex (chatbots)

1. Generative AI

• Bedrock

  • Access to foundation models (Claude, Llama, Stable Diffusion)

  • API integration

  • Model customization

  • Fine-tuning capabilities

• Amazon CodeWhisperer

  • AI-powered coding assistant

  • Code suggestions

  • Security scans

1. Business Solutions

• Forecast (time-series forecasting)

• Fraud Detector

• Personalize (recommendation systems)

• Contact Lens (contact center analytics)

1. AI Infrastructure

Development → Training → Deployment → Monitoring
(SageMaker Studio) (EC2, ECS) (Endpoints) (CloudWatch)

1. Latest Additions:

• Amazon Q (enterprise AI assistant)

• HealthScribe (medical transcription)

• AWS Clean Rooms ML (collaborative ML)

• Titan (AWS foundation models)

Common Integration Pattern:

Data Sources → Data Prep → AI Processing → Business Apps
(S3, RDS)    (Glue)     (SageMaker)    (Applications)
         ↳ Bedrock API calls for GenAI ↗