Large Language Model-Based Solutions: How to Deliver Value with Cost-Effective Generative AI Applications
Shreyas Subramanian
Nov 2024 · Gildan Media · Narrated by Daniel Henning
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11 hr 42 min
Unabridged
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About this audiobook
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
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
About the author
Shreyas Subramanian is a principal data scientist at AWS, one of the largest organizations building and providing large language models for enterprise use. He is currently advising both internal Amazon teams and large enterprise customers on building, tuning, and deploying Generative AI applications at scale.
Daniel Henning is a director, producer, actor, and writer. His work has been seen on HBO, CBS, NBC, ABC, FOX, MTV, Comedy Central, and on stages throughout Southern California. He won a 2017 Telly Award for "Best Writer" for the film version of his play The Tragedy of JFK (as Told by Wm. Shakespeare).
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