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Prompt Engineering for LLMs - John Berryman, Albert Ziegler

Prompt Engineering for LLMs

The Art and Science of Building Large Language Model-Based Applications
Buch | Softcover
250 Seiten
2024
O'Reilly Media (Verlag)
978-1-0981-5615-2 (ISBN)
CHF 109,95 inkl. MwSt
This book will teach you the art and science of prompt engineering-the key to unlocking the true potential of LLMs. Industry experts John Berryman and Albert Ziegler share how to communicate effectively with AI, transforming your ideas into a language model-friendly format. 
Large language models (LLMs) are revolutionizing the world, promising to automate tasks and solve complex problems. A new generation of software applications are using these models as building blocks to unlock new potential in almost every domain, but reliably accessing these capabilities requires new skills. This book will teach you the art and science of prompt engineering-the key to unlocking the true potential of LLMs.

Industry experts John Berryman and Albert Ziegler share how to communicate effectively with AI, transforming your ideas into a language model-friendly format. By learning both the philosophical foundation and practical techniques, you'll be equipped with the knowledge and confidence to build the next generation of LLM-powered applications.

Understand LLM architecture and learn how to best interact with it Design a complete prompt-crafting strategy for an application Gather, triage, and present context elements to make an efficient prompt Master specific prompt-crafting techniques like few-shot learning, chain-of-thought prompting, and RAG

John Berryman started out in Aerospace Engineering but soon found that he was more interested in math and software than in satellites and aircraft. He soon switched to software development, specializing in search and recommendation technologies, and not too long afterward co-authored Relevant Search. At GitHub John played a prominent role in moving code search to a new scalable infrastructure. Subsequently John joined the Data Science team, and then Copilot where he currently provides technical leadership and direction in Prompt Crafting work. Albert Ziegler is a principal machine learning engineer with a PhD in Mathematics and a home at GitHub Next, GitHub's innovation and future group. His main interests are fusion of deductive and intuitive reasoning to improve the software development experience. At GitHub Next, he was part of the trio that conceived and implemented GitHub Copilot, the first large scale product delivering generative AI for software development. His most recent projects include Copilot Radar and AI for Pull Requests.

Erscheinungsdatum
Verlagsort Sebastopol
Sprache englisch
Maße 178 x 233 mm
Themenwelt Informatik Software Entwicklung SOA / Web Services
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Mathematik / Informatik Informatik Web / Internet
ISBN-10 1-0981-5615-3 / 1098156153
ISBN-13 978-1-0981-5615-2 / 9781098156152
Zustand Neuware
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