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Building LLM Powered  Applications

You're reading from   Building LLM Powered Applications Create intelligent apps and agents with large language models

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Product type Paperback
Published in May 2024
Publisher Packt
ISBN-13 9781835462317
Length 342 pages
Edition 1st Edition
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Author (1):
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Valentina Alto Valentina Alto
Author Profile Icon Valentina Alto
Valentina Alto
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Table of Contents (16) Chapters Close

Preface 1. Introduction to Large Language Models 2. LLMs for AI-Powered Applications FREE CHAPTER 3. Choosing an LLM for Your Application 4. Prompt Engineering 5. Embedding LLMs within Your Applications 6. Building Conversational Applications 7. Search and Recommendation Engines with LLMs 8. Using LLMs with Structured Data 9. Working with Code 10. Building Multimodal Applications with LLMs 11. Fine-Tuning Large Language Models 12. Responsible AI 13. Emerging Trends and Innovations 14. Other Books You May Enjoy
15. Index

Summary

In this chapter, we covered the “dark side” of generative AI technologies, exposing its associated risks and biases, such as hallucinations, harmful content, and discrimination. To reduce and overcome those risks, we introduced the concept of Responsible AI, starting with a deep dive into the technical approach we can have while developing LLM-powered applications; we covered the different levels of risk mitigation – model, metaprompt, and UX – and then moved on to the broader topic of institutional regulations. In this context, we examined the advancements that have been carried out by governments in the last year, with a focus on the AI Act.

Responsible AI is an evolving field of research, and it definitely has an interdisciplinary flavor. There will probably be an acceleration at the regulation level to address it in the near future.

In the next and final chapter, we are going to cover all the emerging trends and innovations happening...

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