8 New Artificial General Intelligence Books Reshaping the Industry in 2025

Ray Kurzweil extends his decades-long exploration of artificial intelligence by evaluating his 1999 prediction that AI would reach human-level intelligence by 2029. This book offers you a detailed look at exponential technology growth, including nanotechnology, brain-computer interfaces, and radical life extension, backed by decades of research and real-world examples like nanobots rebuilding matter atom by atom. It examines both the transformative potential and the ethical challenges of merging human intelligence with AI, discussing topics such as AI’s impact on employment and autonomous vehicles. If you want to understand how near-future technologies might reshape humanity and your life, Kurzweil’s insights provide a clear framework, though those seeking purely technical AI methodologies may find it less focused on code and algorithms.

Drawing from his role as an Associate Professor of Computer Science and Engineering at New York University and cofounder of a game AI startup, Julian Togelius offers a focused exploration of how to build AI systems with broad, human-like intelligence. You’ll gain insight into the contrast between narrow AI, which excels in specific tasks, and artificial general intelligence capable of adapting across domains. The book details two core approaches—foundation models through self-supervised learning and open-ended learning in virtual environments—helping you grasp both technical frameworks and their implications. Throughout, Togelius also addresses profound questions about AI consciousness, societal risks, and transformative impacts, making this a thoughtful read if you want a grounded yet forward-looking perspective on AGI.

This tailored book delves into the forefront of Artificial General Intelligence as it stands in 2025, exploring the latest breakthroughs and emerging research shaping the field. It reveals advanced concepts and novel discoveries, focusing sharply on your specific interests and goals within AGI development. By matching your background and areas of curiosity, the content examines cutting-edge techniques and evolving theories that define the state of AGI today. Readers gain a personalized lens on new knowledge, enabling a deep understanding of ongoing innovations and how they relate to your aspirations. This tailored exploration offers a unique opportunity to stay informed on fresh advancements while aligning learning with your objectives.

What if everything you knew about artificial intelligence was missing a crucial piece? Eitan Michael Azoff, blending his neuroscience expertise with AI research, challenges conventional AI approaches by exploring how the brain's visual processing, lateralization, and neuromodulation inform human-level intelligence. You gain insights into complex concepts like diffuse neuronal decision making and the scientific method applied to AI learning cycles, along with an embodied neurorobot model that interacts with the physical world. This book is ideal if you want to understand how neuroscience can concretely shape artificial general intelligence development rather than just theoretical AI models.

Unlike most AI books that focus narrowly on theory, this work dives deep into the practical transitions shaping Artificial General Intelligence today. Drawing from Victor Hugo C. de Albuquerque's editorial experience and expertise in AI, it unpacks machine and deep learning algorithms alongside key applications like computer vision and natural language processing. You'll explore chapters on AI model engineering, evaluation, and deployment, culminating in an insightful look at generative AI and neuromorphic systems. If you're eager to understand the technologies and methods driving advances toward AGI, this book offers a detailed, structured pathway without unnecessary jargon.

Drawing from his extensive research at DeepMind and academic tenure, Marcus Hutter, along with David Quarel and Elliot Catt, presents a rigorous exploration of what it means for an agent to act intelligently in unknown environments. This book delves into the Universal Algorithmic Intelligence framework, introducing AIXI, a theoretical model for optimal reinforcement learning that synthesizes Bayesian inference, decision theory, and algorithmic information theory. You’ll find detailed algorithms and practical approximations, such as Monte Carlo tree search, that bridge theory with implementation. If you’re tackling the mathematical foundations behind artificial intelligence and seeking to understand the boundaries and possibilities of general intelligence, this book offers a challenging yet rewarding path.

This tailored book explores the latest trends and discoveries shaping Artificial General Intelligence in 2025, focusing on your unique interests and background. It delves into emerging AGI research and examines evolving concepts that define the future landscape of intelligent systems. By addressing your specific goals, the book reveals how to anticipate and navigate new developments in AGI with clarity and depth. The personalized approach ensures the content matches your expertise and curiosity, providing a rich learning experience centered on the fast-changing world of general intelligence advancements. You'll uncover insights that keep you ahead in this transformative field, empowering you to engage confidently with tomorrow's AGI challenges.

Daniel Robrecht challenges prevailing views by mapping the intricate journey toward Artificial General Intelligence (AGI), offering a clear-eyed exploration of AI’s evolution and its future possibilities. You’ll learn about the foundational architecture of intelligence, from neural networks to symbolic AI, and the ethical and societal questions AGI raises. The book breaks down complex topics such as consciousness in machines and safety protocols in practical terms, making it accessible if you’re curious about how human-like intelligence in machines might emerge. If you’re invested in AI’s trajectory—whether as a technologist, policymaker, or enthusiast—this concise yet insightful guide will sharpen your understanding of the challenges and promises ahead.

Drawing from his extensive computer science background and deep AI research, Richard A. Mann explores the imminent arrival of superintelligent machines and their profound effects on society. You’ll gain insights into landmark projects like Project Q and Google Pathways, alongside thoughtful discussions on what the technological singularity means for humanity’s future. Chapters delve into ethical dilemmas and preparation strategies for coexistence with AGI, offering you a clear-eyed view of both opportunities and risks. This book suits anyone keen on understanding how accelerating AI innovation reshapes intelligence and societal structures, though it may challenge those expecting straightforward technical manuals.

What makes this book distinct is Jon Adams's ability to bridge decades of IT experience with the complex frontier of Artificial General Intelligence. You’ll explore foundational concepts like neural networks, cognitive architectures, and the nuanced divide between narrow AI and AGI, all explained in accessible language. For example, Adams dedicates chapters to the ethical challenges and future implications of machines mimicking human thought, inviting you to consider not just the technology but its philosophical impact. This book suits anyone curious about AI’s next evolution, especially if you want a grounded, thoughtful introduction without jargon overload.