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Building LLM Powered  Applications

Building LLM Powered Applications

By : Valentina Alto
4.2 (22)
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Building LLM Powered  Applications

Building LLM Powered Applications

4.2 (22)
By: Valentina Alto

Overview of this book

Building LLM Powered Applications delves into the fundamental concepts, cutting-edge technologies, and practical applications that LLMs offer, ultimately paving the way for the emergence of large foundation models (LFMs) that extend the boundaries of AI capabilities. The book begins with an in-depth introduction to LLMs. We then explore various mainstream architectural frameworks, including both proprietary models (GPT 3.5/4) and open-source models (Falcon LLM), and analyze their unique strengths and differences. Moving ahead, with a focus on the Python-based, lightweight framework called LangChain, we guide you through the process of creating intelligent agents capable of retrieving information from unstructured data and engaging with structured data using LLMs and powerful toolkits. Furthermore, the book ventures into the realm of LFMs, which transcend language modeling to encompass various AI tasks and modalities, such as vision and audio. Whether you are a seasoned AI expert or a newcomer to the field, this book is your roadmap to unlock the full potential of LLMs and forge a new era of intelligent machines.
Table of Contents (16 chapters)
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14
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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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