Welcome to Generative AI ATLAS

ATLAS is your trusted generative AI knowledge hub that delivers current, expert-verified technical content for generative AI implementation. Find everything you need, no matter where you are on your journey, from foundational concepts to advanced implementations.

Disclaimer

1. Generative AI Atlas (“ATLAS”) is provided for informational purposes only, and does not constitute legal, regulatory, compliance, or professional advice of any kind, and should not be relied upon as such.
2. You should consider performing your own independent assessment of the information and other content contained in ATLAS to ensure that your use complies with your own specific quality control practices and standards, as well as local rules, laws, regulations, licenses and terms of use that apply to you and your content.

What you'll find here

Every time you visit ATLAS, you can expect content and guidance that is curated, current, and technology-agnostic:

• ✨Curated Excellence: Every piece of content is personally validated by AWS generative AI subject matter experts
• 🔄Always Current: Rigorous maintenance ensures content stays relevant
• 🎯Production-First: Focused on real-world implementation, not just theory
• 🌐Technology-Agnostic: Core generative AI principles, not just AWS-specific solutions

We complement these resources with relevant links to AWS documentation, community projects, and external materials where appropriate. The content is organized into focused sections to help you quickly find what you need for your generative AI journey.

• Generative AI Fundamentals

  Essential principles and foundational knowledge for understanding generative AI, its business value, and implementation considerations.

  Getting started

• Technical Foundations & Key Patterns

  Deep dive into key primitives like prompts and embeddings, explore various generative AI models, and understand core technical concepts.

  Explore foundations

• Architecture & Design Patterns

  Guidance on system design, application architectures, prompt engineering, RAG, scalability, security, and cost optimization for generative AI solutions.

  Explore architectures

• Systematic Path to Production

  A framework outlining business strategy, data foundation, training, governance, responsible AI, SDLC, and operations for generative AI.

  View framework

• Organization Adoption Framework

  Strategic insights on AI vision, CoEs, risk management, change management, and operational scaling for enterprise-wide generative AI adoption.

  Get guidance

• Example Deployments & Reference Code

  Practical examples, industry-specific blueprints, sample implementations with code, and case studies for generative AI solutions.

  Browse implementations

• Resources & Tools

  Discover AWS services, popular tools, libraries, frameworks, and community support for your generative AI projects.

  Discover resources

• ISV Focus

  Guidance for ISVs on building, selling, and operating profitable AI products on AWS, covering COGS, ROI, security, and IP protection.

  Learn more

What's not included

• AWS service-specific content (refer to AWS documentation)
• Comparative analysis of generative AI market offerings
• Workshop/tutorial sample code implementations

Content roadmap

Content is being actively developed and maintained. Areas under development are clearly marked, and we welcome your feedback to help prioritize completion. Review our content roadmap and contribution guide to get started.

How to provide feedback

Help us improve Generative AI Atlas by sharing your insights and reporting issues via GitHub Issues.