This audiobook is narrated by a digital voice.
About this audiobook
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This book delves into the fascinating world of Generative AI, exploring the two key technologies driving its advancements: Large Language Models (LLMs) and Foundation Models (FMs).
Part 1: Foundations
LLMs Demystified: We begin by understanding LLMs, powerful AI models trained on massive amounts of text data. These models can generate human-quality text, translate languages, write different creative formats, and even answer your questions in an informative way.
The Rise of FMs: However, LLMs are just a piece of the puzzle. We explore Foundation Models, a broader category encompassing models trained on various data types like images, audio, and even scientific data. These models represent a significant leap forward in AI, offering a more versatile approach to information processing.
Part 2: LLMs and Generative AI Applications
Training LLMs: We delve into the intricate process of training LLMs, from data acquisition and pre-processing to different training techniques like supervised and unsupervised learning. The chapter also explores challenges like computational resources and data bias, along with best practices for responsible LLM training.
Fine-Tuning for Specific Tasks: LLMs can be further specialized for targeted tasks through fine-tuning. We explore how fine-tuning allows LLMs to excel in areas like creative writing, code generation, drug discovery, and even music composition.
Part 3: Advanced Topics
LLM Architectures: We take a deep dive into the technical aspects of LLMs, exploring the workings of Transformer networks, the backbone of modern LLMs. We also examine the role of attention mechanisms in LLM processing and learn about different prominent LLM architectures like GPT-3 and Jurassic-1 Jumbo.
This audiobook is narrated by a digital voice.
About this audiobook
clear
This book delves into the fascinating world of Generative AI, exploring the two key technologies driving its advancements: Large Language Models (LLMs) and Foundation Models (FMs).
Part 1: Foundations
LLMs Demystified: We begin by understanding LLMs, powerful AI models trained on massive amounts of text data. These models can generate human-quality text, translate languages, write different creative formats, and even answer your questions in an informative way.
The Rise of FMs: However, LLMs are just a piece of the puzzle. We explore Foundation Models, a broader category encompassing models trained on various data types like images, audio, and even scientific data. These models represent a significant leap forward in AI, offering a more versatile approach to information processing.
Part 2: LLMs and Generative AI Applications
Training LLMs: We delve into the intricate process of training LLMs, from data acquisition and pre-processing to different training techniques like supervised and unsupervised learning. The chapter also explores challenges like computational resources and data bias, along with best practices for responsible LLM training.
Fine-Tuning for Specific Tasks: LLMs can be further specialized for targeted tasks through fine-tuning. We explore how fine-tuning allows LLMs to excel in areas like creative writing, code generation, drug discovery, and even music composition.
Part 3: Advanced Topics
LLM Architectures: We take a deep dive into the technical aspects of LLMs, exploring the workings of Transformer networks, the backbone of modern LLMs. We also examine the role of attention mechanisms in LLM processing and learn about different prominent LLM architectures like GPT-3 and Jurassic-1 Jumbo.
Generative AI with Large Language Models: A Comprehensive Guide
Generative AI with Large Language Models: A Comprehensive Guide
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Product Details
| BN ID: | 2940191195094 |
|---|---|
| Publisher: | Anand Vemula |
| Publication date: | 09/21/2024 |
| Edition description: | Unabridged |
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