Herat Joshi – författare

This book investigates the dynamic relationship between artificial general intelligence (AGI) and quantum computing.

This book explores how autonomous AI systems are reshaping human decision-making across various industries and society. The book delves into the concept of Agentic AI—AI systems that can act independently and make decisions without human intervention. Unlike existing literature that speculates about superintelligent systems, this book offers practical insights into how current AI systems are already transforming sectors like health care, finance, and law. It highlights the growing impact of these technologies on professional roles and governance, offering a balanced view of both the opportunities and challenges presented by AI autonomy. The book's findings show that Agentic AI enhances decision-making by improving efficiency, accuracy, and scalability. However, it also presents ethical concerns related to accountability, transparency, and the shifting nature of human responsibility in AI-mediated environments. It emphasizes the need for robust ethical frameworks and governance structures to ensure that AI systems align with human values. By focusing on real-world applications and current AI technologies, the book provides actionable insights for decision-makers, helping businesses, policymakers, and technologists navigate the evolving AI landscape. It offers a roadmap for understanding the present-day capabilities of autonomous systems and prepares professionals for the ethical and operational challenges of integrating these technologies. Readers will gain a comprehensive understanding of how Agentic AI is poised to redefine human life and decision-making, making it essential for anyone interested in the future of technology, ethics, and innovation. Unlike traditional AI, which typically requires human supervision or input, Agentic AI introduces the concept of autonomy—AI systems that can act, learn, and make decisions independently. This paradigm shift challenges the conventional human-centered approach to decision-making, positioning AI as a true partner in complex cognitive tasks. The book also explores the ethical and societal implications of AI autonomy in ways that extend beyond typical discussions.

This book represents a unique and comprehensive resource for understanding the intersection of advanced artificial intelligence (AI) and neurology. By focusing on graph neural networks (GNNs), the book addresses a crucial gap in the current literature, providing valuable insights into the analysis and interpretation of complex brain networks and neurological data. Intended for a diverse audience, including clinicians, scientists, researchers, and students, it demystifies the complexities of GNNs and their applications in neurology. For clinicians and healthcare practitioners, the book illustrates how GNNs can enhance diagnostic accuracy, inform personalized treatment plans and predict disease progression. This leads to improved patient outcomes and a deeper understanding of neurological conditions such as Alzheimer's, Parkinson's, multiple sclerosis and epilepsy. Researchers will find the book particularly valuable as it delves into the methodologies and technical aspects of GNNs, showcasing their ability to handle diverse data sources including genetic, imaging and clinical information. By integrating these datasets, GNNs reveal hidden patterns and biomarkers, offering new avenues for research and potential therapeutic targets.A Guide to Graph Neural Networks for Neurological Disorders addresses the challenge of missing data, a common issue in neurological research, and demonstrates how GNNs can manage and mitigate these gaps. For students, both undergraduate and postgraduate, the book serves as an educational tool, providing clear explanations and practical examples that make complex concepts accessible. It equips the next generation of neuroscientists and data scientists with the knowledge and skills needed to contribute to this rapidly evolving field. The book aims to provide a foundational understanding of GNNs, demonstrate their practical applications in neurology, and inspire further research and innovation. By bridging the gap between AI and medical practice, the book empowers readers to leverage cutting-edge technology in the quest to understand and treat neurological illnesses, ultimately enhancing the quality of care and advancing the field of neuroscience.