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Understanding Large Language Models: Learning Their Underlying Concepts and Technologies Amaratunga Thimira

By:

Thimira Amaratunga

Material type: Text

TextPublication details: SriLanka Apress 2023Description: 156DDC classification:

006.3 AMA

Contents:

NLP Through Ages Transformers What Makes LLMs Large Popular LLMs Threats, Opportunities and Misconceptions

Summary: The book starts with an introduction to the rise of conversational AIs such as ChatGPT, and how they are related to the broader spectrum of large language models. From there, you will learn about natural language processing (NLP), its core concepts, and how it has led to the rise of LLMs. Next, you will gain insight into transformers and how their characteristics, such as self-attention, enhance the capabilities of language modeling, along with the unique capabilities of LLMs. The book concludes with an exploration of the architectures of various LLMs and the opportunities presented by their ever-increasing capabilities--as well as the dangers of their misuse.

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Books	IIITDM Kurnool COMPUTER SCIENCE ENGINEERING	Non-fiction	006.3 AMA (Browse shelf(Opens below))	Available		0005770
Reference	IIITDM Kurnool Reference	Reference	006.3 AMA (Browse shelf(Opens below))	Not For Loan		0005771

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Previous	005.1 SOM Software engineering	005.1 SOM Software engineering	005.1 SOM Software engineering	006.3 AMA Understanding Large Language Models: Learning Their Underlying Concepts and Technologies	338.502 BAY Managerial Economics and Business Strategy	519.11 KOL Discrete mathematical structures	519.11 KOL Discrete mathematical structures	Next

NLP Through Ages
Transformers
What Makes LLMs Large
Popular LLMs
Threats, Opportunities and Misconceptions

The book starts with an introduction to the rise of conversational AIs such as ChatGPT, and how they are related to the broader spectrum of large language models. From there, you will learn about natural language processing (NLP), its core concepts, and how it has led to the rise of LLMs. Next, you will gain insight into transformers and how their characteristics, such as self-attention, enhance the capabilities of language modeling, along with the unique capabilities of LLMs. The book concludes with an exploration of the architectures of various LLMs and the opportunities presented by their ever-increasing capabilities--as well as the dangers of their misuse.

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