Saloni Garg is a Senior Machine Learning Engineer based in Mountain View, California. With deep expertise in scalable ML systems and infrastructure, she has made impactful contributions to open-source projects including Ray and PyTorch. A passionate technologist and community advocate, Saloni has spoken at 18+ international conferences on topics ranging from distributed training to AI safety.
Her work has been recognized globally, she is a recipient of the prestigious Women in Open Source Award by Red Hat and was honored as a Google Venkat Panchapakesan Scholar for her commitment to using technology for social good.
Saloni is driven by a mission to make advanced AI more accessible, explainable, and responsible. This book is her latest effort to bridge cutting-edge AI with real-world applications, empowering engineers, researchers, and enthusiasts to rethink the future of reasoning systems. De Gruyter Brill (04.08.2026)

1. Auflage 03.08.2026 , Englisch

Dieses Buch bietet einen tiefen Einblick in die Grundlagen von RAG und behandelt Transformatorarchitekturen, Vektorähnlichkeitssuche und die Integration von Abruftechniken in generative Modelle. Die Leser lernen, RAG mithilfe von Open Source Tools zu implementieren, erkunden reale Anwendungen in Chatbots, Abrufen von juristischen und medizinischen Dokumenten sowie KI-gestützte Forschung und stellen sich Herausforderungen wie Voreingenommenheit und Fehlinformationen.


This book provides a deep dive into the foundations of RAG, covering transformer architectures, vector similarity search, and the integration of retrieval techniques into generative models. Readers will learn to implement RAG using open-source tools, explore real-world applications in chatbots, legal and medical document retrieval, and AI-assisted research, and address challenges like bias and misinformation. 

ISBN 978-3-11-222677-3 1. Auflage 03.08.2026 69,95 € Portofrei Bestellen (Buch | Softcover)