Safe For Humans AI

Safe For Humans AI

Mark Watson
Buy on Leanpub

Table of Contents

Safe For Humans AI

  • Preface
    • Running Software Examples
    • Technology Stack for Development of the Book Examples
    • Author’s Use of Large Language Models for Writing and Coding
    • The “Big Project Example” in this Book
    • About the Author
    • Book Cover
    • Acknowledgements
  • Part I - Risks Using AI
  • Road Map for Our Journey to Safe AI
    • Your Requirements for Privacy and AI Safety vs. Making Maximum Business Use of LLMs
    • A Prompt Template For Evaluating Safety vs. Opportunity Tradeoffs
  • Risks
    • Don’t Throw the Baby Out With the Bath Water
    • Government Control of AI and International Norms
    • Key Aspects of AI Safety
    • Leaking Customer Data
    • Inaccurate Results from LLMs
    • Legal Exposure to the Use of Possibly Private Data Used to Train LLMs
    • Protecting Your Business Processes from Competition
  • AI Weapons
    • Attempts to Mitigate Risks of AI Weapons
    • What About the United Nations?
  • Generative AI
    • Midjourney
    • Microsoft and GitHub Copilot
    • ChatGPT and Microsoft Bing with ChatGPT
  • Governance
  • Transparency in a World Where Corporations and Governments Do Not Want Transparency
    • Building Transparency Into AI Systems
  • Part II - Using AI Safely: a Technical Approach
  • Portability Library Supporting OpenAI, Hugging Face, and Self Hosted Models
    • Examples Using LlmLib
  • Using Local Large Language Models
    • Available Public Large Language Models
    • StabilityAI’s StableLM Using lil-parrot Library
    • Google’s Flan-T5-XXL
    • Running FastChat with Vicuna LLMs
    • Building a Chat Application Using Text From My Books and Prompt Engineering
  • Fine-Tuning LLMs Using Your Data
    • Fine-Tuning vs. Prompt Engineering
    • The Process of Fine-Tuning
    • Building a Chat Application Using Text From My Books and Fine-Tuning
  • Part III - What Does the Future Hold?
  • AI-Safety Respecting Architectures for Use in Education
  • AI-Safety Respecting Architectures for Use in Small and Medium Size Businesses
  • Trying to Predict the Future
    • Advances in LLMs
    • Small Devices and Edge Computing
    • Personalized AIs
    • New Kinds of Digital Devices
  • A Thought Experiment on Building a Safe AI in Alignment With Positive Human Values
    • A Design Based on Prompt Engineering
    • Safe AI Thought Experiment Implementation
  • Good Luck
  • Appendix A - Using Google Colab
  • Appendix B - Using GPU Servers on Lambda Labs
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Safe For Humans AI

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Safe For Humans AI20 chapters

Begin ›
  1. Preface

  2. Part I - Risks Using AI

  3. Road Map for Our Journey to Safe AI

  4. Risks

  5. AI Weapons

  6. Generative AI

  7. Governance

  8. Transparency in a World Where Corporations and Governments Do Not Want Transparency

  9. Part II - Using AI Safely: a Technical Approach

  10. Portability Library Supporting OpenAI, Hugging Face, and Self Hosted Models

  11. Using Local Large Language Models

  12. Fine-Tuning LLMs Using Your Data

  13. Part III - What Does the Future Hold?

  14. AI-Safety Respecting Architectures for Use in Education

  15. AI-Safety Respecting Architectures for Use in Small and Medium Size Businesses

  16. Trying to Predict the Future

  17. A Thought Experiment on Building a Safe AI in Alignment With Positive Human Values

  18. Good Luck

  19. Appendix A - Using Google Colab

  20. Appendix B - Using GPU Servers on Lambda Labs