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Decoding Large Language Models

You're reading from   Decoding Large Language Models An exhaustive guide to understanding, implementing, and optimizing LLMs for NLP applications

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Product type Paperback
Published in Oct 2024
Publisher Packt
ISBN-13 9781835084656
Length 396 pages
Edition 1st Edition
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Author (1):
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Irena Cronin Irena Cronin
Author Profile Icon Irena Cronin
Irena Cronin
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Table of Contents (22) Chapters Close

Preface 1. Part 1: The Foundations of Large Language Models (LLMs)
2. Chapter 1: LLM Architecture FREE CHAPTER 3. Chapter 2: How LLMs Make Decisions 4. Part 2: Mastering LLM Development
5. Chapter 3: The Mechanics of Training LLMs 6. Chapter 4: Advanced Training Strategies 7. Chapter 5: Fine-Tuning LLMs for Specific Applications 8. Chapter 6: Testing and Evaluating LLMs 9. Part 3: Deployment and Enhancing LLM Performance
10. Chapter 7: Deploying LLMs in Production 11. Chapter 8: Strategies for Integrating LLMs 12. Chapter 9: Optimization Techniques for Performance 13. Chapter 10: Advanced Optimization and Efficiency 14. Part 4: Issues, Practical Insights, and Preparing for the Future
15. Chapter 11: LLM Vulnerabilities, Biases, and Legal Implications 16. Chapter 12: Case Studies – Business Applications and ROI 17. Chapter 13: The Ecosystem of LLM Tools and Frameworks 18. Chapter 14: Preparing for GPT-5 and Beyond 19. Chapter 15: Conclusion and Looking Forward 20. Index 21. Other Books You May Enjoy

Legal challenges in LLM deployment and usage

Addressing the legal challenges associated with the deployment and usage of LLMs is critical, as these systems increasingly affect various aspects of society and commerce. In this section, we will take a closer look at the two main legal areas.

Intellectual property rights and AI-generated content

The topic of intellectual property (IP) rights in the context of AI-generated content is complex and still an emerging area of law. The creation of content by LLMs raises several challenging questions regarding the ownership and control of IP. Here’s an in-depth look into the different facets of this issue:

  • Ownership of AI-generated content:
    • Legal precedents: Historically, IP law has been built around the idea of human authorship. AI challenges this notion because it can generate content independently after being initially programmed by humans.
    • Human versus machine: Most current legal frameworks do not recognize AI as an independent...
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