Foundations of Artificial Intelligence Agents — Part 1: LLM Agents
In the ever-evolving landscape of technology, artificial intelligence has experienced unprecedented growth, propelled by breakthroughs such as deep learning and the accessibility of cutting-edge hardware and software. From the advent of powerful GPUs to the emergence of machine learning libraries like TensorFlow and PyTorch, the journey has now led us to the era of generative AI and the remarkable presence of ChatGPT.
Foundations of Artificial Intelligence Agents delves into this transformative journey, offering insights into the rapid advancements of autonomous agents. The book explores the integration of large language models, reinforcement learning, and other sophisticated approaches, providing a comprehensive look at the exciting developments that bring us closer to the prospect of practical AI assistants, co-pilots, and potential co-workers.
Table of Contents
- Chapter 1Introduction to AI and LLM Agents
- Chapter 2Fundamentals of Large Language Models
- Chapter 3Multi-Modal Models
- Chapter 4LLM Agents and Reasoning
- Chapter 5LLM Agents and Planning
- Chapter 6LLM Agents with Actions and Tools
- Chapter 7LLM Agents with External Memory and Retrieval
- Chapter 8Multi-LLM Agents
- Chapter 9Building and Deploying LLM Agents
- Chapter 10Applications of LLM Agents
- Chapter 11Conclusion
- AppendixTools and Frameworks for LLM Development (online)
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