Part 4: Issues, Practical Insights, and Preparing for the Future

In this part, you will learn about identifying and mitigating risks, confronting biases in LLMs, legal challenges in LLM deployment and usage, regulatory landscape and compliance, and ethical considerations. We will provide you with business case studies from which you will learn the concept of ROI. Additionally, you will see a survey of the landscape of AI tools, a comparison between open source and proprietary tools, an explanation of how to integrate LLMs with existing software stacks, and an exploration of the role of cloud providers in NLP. You will learn about what to expect from the next generation of LLMs and how to get ready for GPT-5 and beyond. We will conclude with key takeaways from this guide, the future trajectory of LLMs in NLP, and final thoughts about the LLM revolution.

This part contains the following chapters:

• Chapter 11, LLM Vulnerabilities, Biases, and Legal Implications
• Chapter 12...