Trustworthy Generative AI

LLM Evaluation and Alignment, The Foundational Ideas teaches you to think of evaluation as a design constraint. You’ll employ a "working backwards" methodology that begins with what your system must get right, which directs you to the appropriate evaluation approach. As you internalize the define > evaluate > analysis > align cycle, you’ll start making more informed tradeoffs and expertly balancing helpfulness, safety, and brand voice in your models.

AI agents are showing up everywhere—and most of them are being built by trial and error. Agent Design Patterns distills the experience of a growing community of agent builders into 20+ composable, reusable patterns for building AI agents that are reliable, efficient, controllable, and easy to reason about. In this uniquely valuable book, author and NVIDIA Research scientist <b>Peter Belcak</b> gives you a durable engineering vocabulary and design intuition that outlasts any new model release.

Introduction to Generative AI, Second Edition is a completely revised and updated guide to the capabilities, risks, and limitations of generative AI. You’ll understand the latest innovations in AI, AI agents, multimodal training, reasoning models, retrieval-augmented generation (RAG), and more. Along the way, you’ll explore how AI is impacting the world, with an expert-level look at AI in industry, education, and society.

LLMs in Production teaches you how to develop an LLMOps plan that can take an AI app smoothly from design to delivery. You’ll learn techniques for preparing an LLM dataset, cost-efficient training hacks like LORA and RLHF, and industry benchmarks for model evaluation. Along the way, you’ll put your new skills to use in three exciting example projects: creating and training a custom LLM, building a VSCode AI coding extension, and deploying a small model to a Raspberry Pi.