Large Language Model-Based Solutions

How to Deliver Value with Cost-Effective Generative AI Applications

By: Shreyas Subramanian

Narrated by: Daniel Henning

In Large Language Model-Based Solutions: How to Deliver Value with Cost-Effective Generative AI Applications, Principal Data Scientist at Amazon Web Services, Shreyas Subramanian, delivers a practical guide for developers and data scientists who wish to build and deploy cost-effective large language model (LLM)-based solutions. In the book, you'll find coverage of a wide range of key topics, including how to select a model, pre- and post-processing of data, prompt engineering, and instruction fine-tuning.

The author sheds light on techniques for optimizing inference, like model quantization and pruning, as well as different and affordable architectures for typical generative AI (GenAI) applications, including search systems, agent assists, and autonomous agents. You'll also find:

● Effective strategies to address the challenge of the high computational cost associated with LLMs

● Assistance with the complexities of building and deploying affordable generative AI apps, including tuning and inference techniques

● Selection criteria for choosing a model, with particular consideration given to compact, nimble, and domain-specific models

©2024 John Wiley & Sons, Inc. (P)2024 Ascent Audio

No added pdf

Couldn’t find attached pdf it would’ve been very helpful with this book, especially schematic graphs.
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Attached documents are not uploaded , so most of the explanation of processes are hard to follow without it

Attached pdf is neither uploaded to the application nor to the website . Overall the book is very rich and great but needs those materials for more information and great acquisition.