Welcome to our AI playbook! #
This is your go-to resource for staying updated on the rapidly evolving field of AI technology. Here is what we cover:
- Introduction
- Purpose of the Playbook
- How to use this Playbook
- Acknowledgments and Community Contributions
- Understanding AI
- The origins and evolution of AI
- Key Concepts and Terminology
- AI vs. Machine Learning vs. Deep Learning
- Generative AI, LLMs, Agents
- Generative AI Fundamentals
- LLMs and Foundational Models
- Architecture for LLM Applications
- Prompting and Prompt Engineering
- Tokens and Optimization
- Hallucinations and other risks
- Applying AI
- Continuum for Applied AI
- 11 ways to apply Gen AI
- AI Chatbots
- AI Assistants – Copilots
- Human in the loop automation
- Autonomous AI
- AI Use Cases
- Industry-Specific Use Cases (e.g., Healthcare, Finance, Manufacturing, Retail)
- Functional Use Cases (e.g., Customer Service, Sales, Operations, HR)
- AI Tools and Technologies
- Cloud-Based AI Services and Platforms
- Automation Tools for AI Implementation
- Data Management and Preparation for AI
- AI Strategies
- Developing a Successful AI Strategy
- Identifying AI Opportunities and Challenges
- Building a business case for AI
- Strategies for scaling AI initiatives
- Case studies of successful AI strategies
- AI Governance
- AI security: protecting data and systems
- Data governance: ensuring data integrity and accessibility
- The regulatory landscape for AI
- Strategies for managing AI risks
- Creating responsible AI: trust, transparency, and accountability.
- AI Implementation
- AI Implementation life cycle
- Establishing a culture of AI in an organization
- Evaluating AI Vendor Solutions
- Managing AI Projects and Risks
- Resources and Further Learning
- Recommended Books, Websites, and Blogs
- Online Courses and Training Programs
- AI Conferences and Events