Artificial General Intelligence Vs Generative Ai
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Interplay of Artificial General Intelligence with Quantum Computing
Author: C. Kishor Kumar Reddy
language: en
Publisher: Springer Nature
Release Date: 2025-08-12
This book investigates the dynamic relationship between artificial general intelligence (AGI) and quantum computing. AGI refers to a form of AI capable of performing any intellectual task that a human can, while quantum computing utilizes quantum mechanics principles to process information in fundamentally different ways compared to classical computing. This interplay explores how quantum computing might enhance AGI by accelerating complex computations and optimizing learning algorithms, potentially enabling AGI systems to solve problems beyond the reach of traditional computers. It also examines the challenges and opportunities presented by combining these technologies, including theoretical implications and practical applications in advancing AI capabilities. This book examines the groundbreaking intersection of artificial general intelligence (AGI) and quantum computing. The book explores how AGI, which aims to replicate human-like cognitive abilities, can be enhanced by quantum computing's unique processing capabilities. It delves into theoretical foundations, practical applications, and potential synergies, illustrating how quantum computing could tackle complex computational challenges inherent in AGI development. By integrating these advanced technologies, the book provides a comprehensive analysis of their combined impact, offering insights into future advancements and the transformative potential of merging AGI with quantum computing.
Artificial General Intelligence
Author: Kristinn R. Thórisson
language: en
Publisher: Springer Nature
Release Date: 2024-07-16
This book constitutes the refereed proceedings of the 17th International Conference on Artificial General Intelligence, AGI 2024, held in Seattle, Washington, USA in August 2024. The 25 papers presented in this book were carefully reviewed and selected from 55 submissions. The papers focus on the main theme of AGI 2024: 'Understanding Artificial General Intelligence', with discussions on various central concepts of general intelligence including thought, understanding, meaning, creativity, insight, reasoning, autonomy, attention and control.
Future Research Opportunities for Artificial Intelligence in Industry 4.0 and 5.0
Author: Jayesh Rane
language: en
Publisher: Deep Science Publishing
Release Date: 2024-10-14
Artificial intelligence (AI), machine learning (ML) and other emerging technologies such as cloud, edge and quantum computing are converging to rewrite the landscape of modern industries and society as a whole. Comprehensive in scope, the book offers a detailed account of these inter-related domains current trends and future possibilities. Chapter 1: We begin by setting the stage with an overview on various trends, problems proposed to solve and road ahead provided by AI, Machine Learning and Deep learning from cloud, edge and quantum computing perspectives. The same is a comprehensive summary to provide perspective on the implications as one continuous stream of technology. It then discusses scalable and adaptive deep learning algorithms, which work in modern machine learning systems where there is a deluge of data. These algorithms sufficiently prepare AI technologies to face the challenges of increasing data as well as expansion of computational capabilities. Chapter three is Federated learning for Edge AI further makes privacy / personalization and security stronger. The amalgamation of blockchain emphasizes the robust and distributed nature of edge intelligence in modern IoT ecosystems. One of the most pressing issues in today's ethical landscape is that of Explainable Artificial Intelligence (XAI), and so the fourth chapter deals with some recent advances in explaining black-box models, providing a way to better understand -and thus potentially trust- AI-driven decision-making processes. This study explores the application of Automated Machine Learning (AutoML) in the contexts of Industry 4.0 and Society 5.0 giving insights on how automation can bring efficiency and innovation in different sectors. It also presents information on the challenges and opportunities that AutoML faces. In conclusion, the book discusses Artificial General Intelligence (AGI), which is a new topic that presents an ambitious view of what AI may be capable of in the future and some points to digest over how the concept might relate to our understanding on what industry may look like in the next stage of human evolution. Individually, these chapters offer a slice of the overall picture of where AI technologies are headed to keep pace with an advancing world.