دانلود کتاب هوش مصنوعی مولد و مدل‌های زبانی بزرگ: فرصت‌ها، چالش‌ها و کاربردها – جلد ۲

The rapid emergence of Generative AI and Large Language Models (LLMs) has marked a definitive inflection point in the trajectory of artificial intelligence. We have moved beyond the era of static models and simple prediction into a landscape where AI systems can create, reason, and act. This profound shift is reshaping the boundaries of what is possible, from generating diverse content forms to executing complex, autonomous workflows. Generative AI and Large Language Models: Opportunities, Challenges, and Applications—Volume 2 captures this dynamic evolution, offering a comprehensive and rigorously curated exploration of the field’s frontier. Building on the foundations laid in the first volume, a central theme of this second edition is the rise of Agentic AI, witnessing a transition from passive tools to active agents capable of autonomous decision-making. This shift is highlighted by ground-breaking discussions on “Agent Operating Systems (Agent-OS),” which propose a novel substrate for reliable and scalable agent deployment. Security remains a paramount concern as agents are given more agency; chapters on Agentic Cybersecurity Systems dissect the trade-offs in architecture required to secure these autonomous entities. The volume further explores multimodal generative intelligence, examining the fusion of modalities beyond text and logic. The synergy between LLMs and GANs (Generative Adversarial Networks) bridges language and multi-modal generation, creating new frontiers in healthcare applications. Furthermore, the integration of Spiking Neural Networks with generative avatars and advancements in audio-visual speech enhancement demonstrate the field’s push toward more biologically plausible and multimodal intelligence. Addressing the domain of healthcare, the book highlights the necessity of building systems that are not only intelligent but also culturally and clinically grounded. The inclusion of frameworks for Culturally Adaptive AI underscores the importance of context-aware systems, specifically addressing the nuanced needs of regions like the MENA. The text also traces the evolution from Vision-Language Models (VLMs) to autonomous Agentic Graph Reasoning in dermatology. These chapters present self-correcting diagnostic agents grounded in structured Knowledge Graphs, offering explainable and trustworthy AI (XAI) to overcome the “black box” limitations of standard LLMs. Finally, the manuscript examines the deployment of applied generative AI technologies across diverse engineering domains. Real-world applications ground the theoretical discussions, beginning with an exploration of chatbot-assisted soft-ware testing that proposes intelligent automation strategies to address the growing complexity of software ecosystems. The focus then shifts to the evolution of Generative AI in meshes and CAD for geometric intelligence. The volume concludes with an analysis of the optimization of Retrieval-Augmented Generation (RAG) systems for high-performance knowledge retrieval. This book is intended for researchers, practitioners, and students who seek to look beyond the hype and understand the engineering, ethics, and architectures driving the next generation of AI. It consolidates fragmented insights into a unified reference, offering a roadmap through the exhilarating and complex terrain of Generative AI. We extend our deepest gratitude to the authors for their innovative contributions and to the reviewers for their diligence in ensuring the high quality of this work. We hope this volume serves as both a reference and an inspiration for those building the future of intelligence.