AI Engineering: Building Applications with Foundation Models

AI Engineering: Building the Future with Foundation Models

AI is no longer the exclusive domain of research labs. Recent breakthroughs, especially the rise of "model-as-a-service," have democratized access to powerful AI capabilities. This book is your guide to AI Engineering: the practical discipline of building real-world applications using readily available foundation models. It's a field that goes beyond traditional machine learning, demanding a new skillset and a new way of thinking.

Forget training models from scratch. AI Engineering is about leveraging pre-trained giants – powerful foundation models that can understand language, generate images, and much more. This book will show you how to harness their power, even if you don't have a PhD in AI.

We'll start by defining AI Engineering, contrasting it with traditional ML, and introducing the modern "AI stack" – the infrastructure and tools that make it all possible. Crucially, we'll emphasize the importance of evaluation. As AI's power grows, so does the potential for unintended consequences. This book will equip you with the knowledge to build responsible AI, including cutting-edge techniques like using AI to evaluate AI ("AI-as-a-Judge").

You'll learn a practical framework for developing AI applications, starting with the fundamentals and progressing to advanced techniques. We'll cover:

The AI Engineering Process: Understand the steps, challenges, and solutions involved in building an AI application from start to finish.

Model Adaptation: Master techniques like prompt engineering, Retrieval-Augmented Generation (RAG), fine-tuning, agents, and dataset engineering – learn how and why they work.

Deployment and Optimization: Conquer the practical hurdles of latency and cost, ensuring your application is both efficient and effective.

Strategic Choices: Navigate the vast landscape of models, datasets, and benchmarks to make informed decisions for your specific needs.

This book is your practical guide to building the next generation of AI-powered applications. It is useful for the engineers and the product managers.