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Generative AI and Large Language Models: Opportunities, Challenges, and Applications

Cover von Generative AI and Large Language Models: Opportunities, Challenges, and Applications

Volume 2, Studies in Computational Intelligence 1287

Anis Koubaa/Adel Ammar/Lahouari Ghouti et al

Springer Verlag GmbH

192.59

(inklusive MwSt.)

Verfügbarkeit: Noch nicht erschienen, Bestellung ist vorgemerkt

Zusatztext

This book propels the conversation from static models to autonomous, agentic systems. As AI transitions from a tool for generation to a platform for action, this book offers a critical roadmap for the next frontier: Agentic AI. At the heart of this book is the concept of Agent Operating Systems, a revolutionary architecture designed to govern, secure, and scale autonomous agents. This book explores the engineering behind these systems, delving into Agentic Cybersecurity Systems and the architectural trade-offs required for billions of interacting agents. Beyond foundational systems, this book bridges modalities in Multimodal Generative Intelligence, showcasing the synergy between LLMs, GANs, and neuromorphic computing to create responsive, multimodal avatars. A dedicated section on AI for Healthcare presents culturally adaptive tools for the MENA region and advanced Agentic Graph Reasoning for dermatological diagnosis, where self-correcting agents leverage Knowledge Graphs to ensure explainability. Realworld applications continue in Applied Generative AI, where the book covers the optimization of RetrievalAugmented Generation (RAG) systems, the evolution of geometric intelligence in CAD and Meshes, and intelligent chatbotassisted software testing. This book is essential reading for researchers and engineers building the future of intelligencewhere AI not only speaks but acts. Prof. Anis Koubaa, Prof. Adel Ammar, Prof. Wadii Boulila, Prof. Lahouari Ghouti, Prof. Bilel Benjdira Editors Alfaisal University, Riyadh, Saudi Arabia February 2026

Weitere Details

Erschienen: 03.08.2026

Umfang: viii, 313 S., 6 s/w Illustr., 62 farbige Illustr.,

Sprache: ENG

Einband: GEB

ISBN/EAN: 9783032240125

Umbreit-Nr.: 516471

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