AI Engineering: Building Applications with Foundation Models (Paperback)
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Description
Recent breakthroughs in AI have not only increased
demand for AI products, they've also lowered the barriers to entry for those
who want to build AI products. The model-as-a-service approach has transformed
AI from an esoteric discipline into a powerful development tool that anyone can
use. Everyone, including those with minimal or no prior AI experience, can now
leverage AI models to build applications. In this book, author Chip Huyen
discusses AI engineering: the process of building applications with readily
available foundation models.
The book starts with an overview of AI engineering,
explaining how it differs from traditional ML engineering and discussing the
new AI stack. The more AI is used, the more opportunities there are for
catastrophic failures, and therefore, the more important evaluation becomes.
This book discusses different approaches to evaluating open-ended models,
including the rapidly growing AI-as-a-judge approach.
AI application developers will discover how to
navigate the AI landscape, including models, datasets, evaluation benchmarks,
and the seemingly infinite number of use cases and application patterns. You'll
learn a framework for developing an AI application, starting with simple
techniques and progressing toward more sophisticated methods, and discover how
to efficiently deploy these applications.
·
Understand what AI engineering is and how it differs from traditional machine
learning engineering
·
Learn the process for developing an AI application, the challenges at
each step, and approaches to address them
·
Explore various model adaptation techniques, including prompt
engineering, RAG, fine-tuning, agents, and dataset engineering, and understand
how and why they work
·
Examine the bottlenecks for latency and cost when serving foundation
models and learn how to overcome them
·
Choose the right model, dataset, evaluation benchmarks, and metrics for
your needs
Chip Huyen works to accelerate data analytics on GPUs at Voltron Data. Previously, she was with Snorkel AI and NVIDIA, founded an AI infrastructure startup, and taught Machine Learning Systems Design at Stanford. She's the author of the book Designing Machine Learning Systems, an Amazon bestseller in AI.
| Author(s): | Huyen, Chip |
|---|---|
| Book Type: | New Book |
| Genre: | Computers, Artificial Intelligence, Computer Vision & Pattern Recognition, Computer Engineering |
| Format: | Paperback |
| ISBN-10: | 1098166302 |
| EAN: | 9781098166304 |
| Language: | English |
| Number of Pages: | 532 |
| Publication Date: | 2025-01-07 |
| Publisher: | O'Reilly Media |
| Weight: | 2.05 Pounds |
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