LLM Book 10 - Ethics and Challenges of Large Language Models for Absolute Beginners
Table of Contents
1. Introduction
1.1 What are Large Language Models?
1.2 Why are they Important?
1.3 What are the Ethical and Social Issues?
1.4 How to Use this Book?
2. Bias and Fairness
2.1 What is Bias and How does it Affect Language Models?
2.2 How to Measure and Mitigate Bias?
2.3 What is Fairness and How to Achieve it?
2.4 Case Studies and Examples
3. Robustness and Reliability
3.1 What is Robustness and Why is it Important?
3.2 How to Evaluate and Improve Robustness?
3.3 What are the Risks and Challenges of Non-Robust Models?
3.4 Case Studies and Examples
4. Scalability and Efficiency
4.1 What is Scalability and Why is it Important?
4.2 How to Train and Deploy Large Language Models Efficiently?
4.3 What are the Environmental and Economic Impacts of Large Language Models? 4.4 Case Studies and Examples
5. Conclusion
5.1 Summary of the Main Points
5.2 Future Directions and Challenges
5.3 Recommendations and Best Practices
5.4 Further Resources and References
