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This book explores the revolutionary intersection of Generative AI (GenAI) and cybersecurity. It presents a comprehensive guide that intertwines theories and practices, aiming to equip cybersecurity professionals, CISOs, AI researchers, developers, architects and college students with an understanding of GenAI's profound impacts on cybersecurity. The scope of the book ranges from the foundations of GenAI, including underlying principles, advanced architectures, and cutting-edge research, to specific aspects of GenAI security such as data security, model security, application-level security, and the emerging fields of LLMOps and DevSecOps. It explores AI regulations around the globe, ethical considerations, the threat landscape, and privacy preservation. Further, it assesses the transformative potential of GenAI in reshaping the cybersecurity landscape, the ethical implications of using advanced models, and the innovative strategies required to secure GenAI applications. Lastly, the book presents an in-depth analysis of the security challenges and potential solutions specific to GenAI, and a forward-looking view of how it can redefine cybersecurity practices. By addressing these topics, it provides answers to questions on how to secure GenAI applications, as well as vital support with understanding and navigating the complex and ever-evolving regulatory environments, and how to build a resilient GenAI security program. The book offers actionable insights and hands-on resources for anyone engaged in the rapidly evolving world of GenAI and cybersecurity.

This book constitutes the refereed proceedings of the 15th International Conference on Artificial General Intelligence, AGI 2022, held as a hybrid event in Seattle, WA, USA, in August 2022.The 31 full papers presented in this book were carefully reviewed and selected from 61 submissions. The papers cover topics from foundations of AGI, to AGI approaches and AGI ethics, to the roles of systems biology, goal generation, and learning systems, and so much more. Additionally, this volume contains 13 posters.

This book constitutes the refereed proceedings of the 14th International Conference on Artificial General Intelligence, AGI 2021, held as a hybrid event in San Francisco, CA, USA, in October 2021.The 36 full papers presented in this book were carefully reviewed and selected from 50 submissions. The papers cover topics from foundations of AGI, to AGI approaches and AGI ethics, to the roles of systems biology, goal generation, and learning systems, and so much more.

This book constitutes the refereed proceedings of the 13th International Conference on Artificial General Intelligence, AGI 2020, held in St. Petersburg, Russia, in September 2020.The 30 full papers and 8 short papers presented in this book were carefully reviewed and selected from 60 submissions. The papers cover topics such as AGI architectures, artificial creativity and AI safety, transfer learning, AI unification and benchmarks for AGI.

This book constitutes the refereed proceedings of the 12th International Conference on Artificial General Intelligence, AGI 2019, held in Shenzhen, China, in August 2019. The 16 full papers and 5 poster papers presented in this book were carefully reviewed and selected from 30 submissions. The papers are covering AGI architectures, discussing mathematical foundations, philosophical foundations, safety and ethics, and developing ideas from neuroscience and cognitive science.

This book constitutes the proceedings of the 11th International Conference on Artificial General Intelligence, AGI 2018, held in Prague, Czech Republic, in August 2018. The 19 regular papers and 10 poster papers presented in this book were carefully reviewed and selected from 52 submissions. The conference encourage interdisciplinary research based on different understandings of intelligence, and exploring different approaches. As the AI field becomes increasingly commercialized and well accepted, maintaining and emphasizing a coherent focus on the AGI goals at the heart of the field remains more critical than ever.

This book constitutes the refereed proceedings of the Second International Conference on Intelligence Science, ICIS 2017, held in Shanghai, China, in October 2017.The 38 full papers and 9 short papers presented were carefully reviewed and selected from 82 submissions. They deal with key issues in intelligence science and have been organized in the following topical sections: theory of intelligence science; cognitive computing; big data analysis and machine learning; machine perception; intelligent information processing; and intelligent applications.

This book constitutes the proceedings of the 10th International Conference on Artificial General Intelligence, AGI 2017, held in Melbourne, VIC, Australia, in August 2017. The 24 regular papers presented in this book together with 1 short paper were carefully reviewed and selected from 35 submissions. They cover topics such as architectures; mathematical foundations; algorithms; safety; understanding; human cognition; and philosophy.

This book constitutes the refereed proceedings of the 9th International Conference on Artificial General Intelligence, AGI 2016, held in New York City, NY, USA, in July 2016 as part of HLAI 2016, the Joint Multi-Conference on Human-Level Artificial Intelligence 2016. The 24 full papers, 2 short papers, and 10 poster papers presented were carefully reviewed and selected from 67 submissions. AGI research differs from the ordinary AI research by stressing on the versatility and wholeness of intelligence, and by carrying out the engineering practice according to an outline of a system comparable to the human mind inSelf a certain sense.

This book constitutes the refereed proceedings of the 8th International Conference on Artificial General Intelligence, AGI 2015, held in Berlin, Germany in July 2015. The 41 papers were carefully reviewed and selected from 72 submissions. The AGI conference series has played and continues to play, a significant role in this resurgence of research on artificial intelligence in the deeper, original sense of the term of “artificial intelligence”. The conferences encourage interdisciplinary research based on different understandings of intelligence and exploring different approaches. AGI research differs from the ordinary AI research by stressing on the versatility and wholeness of intelligence and by carrying out the engineering practice according to an outline of a system comparable to the human mind in a certain sense.

'Psi'is the term used by researchers for a variety of demonstrable but elusive psychic phenomena. This collection of essays provides a detailed survey of the evidence for psi at the level of scientific examination. Key features of apparent psi phenomena are reviewed, including precognition and remote perception (knowledge of future or distant events that cannot be inferred from present information), presentiment (physiological responses to stimuli that have not yet occurred), the effects of human emotions on globally dispersed machines, the possible impact of local sidereal time on psi performance, and the familiar feeling of knowing who is calling on the phone. Special attention is given to those phenomena that make it difficult for scientists to get a clear understanding of psi. The body of psi research, while complex and frustrating, is shown to contain sufficiently compelling positive evidence to convince the rational open-minded observer that psi is real, and that one or more physical processes probably underlie observed psi phenomena.

The work outlines a detailed blueprint for the creation of an Artificial General Intelligence system with capability at the human level and ultimately beyond, according to the Cog Prime AGI design and the Open Cog software architecture.

The work outlines a novel conceptual and theoretical framework for understanding Artificial General Intelligence and based on this framework outlines a practical roadmap for the development of AGI with capability at the human level and ultimately beyond.

This book constitutes the refereed proceedings of the 7th International Conference on Artificial General Intelligence, AGI 2014, held in Quebec City, QC, Canada, in August 2014. The 22 papers and 8 posters were carefully reviewed and selected from 65 submissions. Researchers have recognized the necessity of returning to the original goals of the field by treating intelligence as a whole. Increasingly, there is a call for a transition back to confronting the more difficult issues of'human-level intelligence'and more broadly artificial general intelligence. AGI research differs from the ordinary AI research by stressing on the versatility and wholeness of intelligence and by carrying out the engineering practice according to an outline of a system comparable to the human mind in a certain sense. The AGI conference series has played and continues to play, a significant role in this resurgence of research on artificial intelligence in the deeper, original sense of the term of'artificial intelligence'. The conferences encourage interdisciplinary research based on different understandings of intelligence and exploring different approaches.

0. 0 Psychology versus Complex Systems Science Over the last century, psychology has become much less of an art and much more of a science. Philosophical speculation is out; data collection is in. In many ways this has been a very positive trend. Cognitive science (Mandler, 1985) has given us scientific analyses of a variety of intelligent behaviors: short-term memory, language processing, vision processing, etc. And thanks to molecular psychology (Franklin, 1985), we now have a rudimentary understanding of the chemical processes underlying personality and mental illness. However, there is a growing feeling-particularly among non-psychologists (see e. g. Sommerhoff, 1990) - that, with the new emphasis on data collection, something important has been lost. Very little attention is paid to the question of how it all fits together. The early psychologists, and the classical philosophers of mind, were concerned with the general nature of mentality as much as with the mechanisms underlying specific phenomena. But the new, scientific psychology has made disappointingly little progress toward the resolution of these more general questions. One way to deal with this complaint is to dismiss the questions themselves. After all, one might argue, a scientific psychology cannot be expected to deal with fuzzy philosophical questions that probably have little empirical signifi­ cance. It is interesting that behaviorists and cognitive scientists tend to be in agreement regarding the question of the overall structure of the mind.

This book summarizes a network of interrelated ideas which I have developed, off and on, over the past eight or ten years. The underlying theme is the psychological interplay of order and chaos. Or, to put it another way, the interplay of deduction and induction. I will try to explain the relationship between logical, orderly, conscious, rule-following reason and fluid, self­ organizing, habit-governed, unconscious, chaos-infused intuition. My previous two books, The Structure of Intelligence and The Evolving Mind, briefly touched on this relationship. But these books were primarily concerned with other matters: SI with constructing a formal language for discussing mentality and its mechanization, and EM with exploring the role of evolution in thought. They danced around the edges of the order/chaos problem, without ever fully entering into it. My goal in writing this book was to go directly to the core of mental process,'where angels fear to tread'-- to tackle all the sticky issues which it is considered prudent to avoid: the nature of consciousness, the relation between mind and reality, the justification of belief systems, the connection between creativity and mental illness,.... All of these issues are dealt with here in a straightforward and unified way, using a combination of concepts from my previous work with ideas from chaos theory and complex systems science.

Creating Internet Intelligence is an interdisciplinary treatise exploring the hypothesis that global computer and communication networks will one day evolve into an autonomous intelligent system, and making specific recommendations as to what engineers and scientists can do today to encourage and shape this evolution. A general theory of intelligent systems is described, based on the author's previous work; and in this context, the specific notion of Internet intelligence is fleshed out, in its commercial, social, psychological, computer-science, philosophical, and theological aspects. Software engineering work carried out by the author and his team over the last few years, aimed at seeding the emergence of Internet intelligence, is reviewed in some detail, including the Webmind AI Engine, a uniquely powerful Internet-based digital intelligence, and the Webworld platform for peer-to-peer distributed cognition and artificial life. The book should be of interest to computer scientists, philosophers, and social scientists, and more generally to anyone concerned about the nature of the mind, or the evolution of computer and Internet technology and its effect on human life.

This book constitutes the refereed proceedings of the 5th International Conference on Artificial General Intelligence, AGI 2012, held in Oxford, UK, in December 2012. The 34 revised full papers presented together with 4 invited keynote lectures were carefully reviewed and selected from 80 submissions. The papers are written by leading scientists involved in research and development of AI systems possessing general intelligence at the human level and beyond; with a special focus on humanoid robotics and AGI, cognitive robotics, creativity and AGI, the future evolution of advanced AGIs, and the dynamics of AGI goal systems.

This book is a collection of writings by active researchers in the field of Artificial General Intelligence, on topics of central importance in the field. Each chapter focuses on one theoretical problem, proposes a novel solution, and is written in sufficiently non-technical language to be understandable by advanced undergraduates or scientists in allied fields. This book is the very first collection in the field of Artificial General Intelligence (AGI) focusing on theoretical, conceptual, and philosophical issues in the creation of thinking machines. All the authors are researchers actively developing AGI projects, thus distinguishing the book from much of the theoretical cognitive science and AI literature, which is generally quite divorced from practical AGI system building issues. And the discussions are presented in a way that makes the problems and proposed solutions understandable to a wide readership of non-specialists, providing a distinction from the journal and conference-proceedings literature. The book will benefit AGI researchers and students by giving them a solid orientation in the conceptual foundations of the field (which is not currently available anywhere); and it would benefit researchers in allied fields by giving them a high-level view of the current state of thinking in the AGI field. Furthermore, by addressing key topics in the field in a coherent way, the collection as a whole may play an important role in guiding future research in both theoretical and practical AGI, and in linking AGI research with work in allied disciplines

The general problem addressed in this book is a large and important one: how to usefully deal with huge storehouses of complex information about real-world situations. Every one of the major modes of interacting with such storehouses – querying, data mining, data analysis – is addressed by current technologies only in very limited and unsatisfactory ways. The impact of a solution to this problem would be huge and pervasive, as the domains of human pursuit to which such storehouses are acutely relevant is numerous and rapidly growing. Finally, we give a more detailed treatment of one potential solution with this class, based on our prior work with the Probabilistic Logic Networks (PLN) formalism. We show how PLN can be used to carry out realworld reasoning, by means of a number of practical examples of reasoning regarding human activities inreal-world situations.

Abstract In this chapter we provide an overview of probabilistic logic networks (PLN), including our motivations for developing PLN and the guiding principles underlying PLN. We discuss foundational choices we made, introduce PLN knowledge representation, and briefly introduce inference rules and truth-values. We also place PLN in context with other approaches to uncertain inference. 1.1 Motivations This book presents Probabilistic Logic Networks (PLN), a systematic and pragmatic framework for computationally carrying out uncertain reasoning – r- soning about uncertain data, and/or reasoning involving uncertain conclusions. We begin with a few comments about why we believe this is such an interesting and important domain of investigation. First of all, we hold to a philosophical perspective in which “reasoning” – properly understood – plays a central role in cognitive activity. We realize that other perspectives exist; in particular, logical reasoning is sometimes construed as a special kind of cognition that humans carry out only occasionally, as a deviation from their usual (intuitive, emotional, pragmatic, sensorimotor, etc.) modes of thought. However, we consider this alternative view to be valid only according to a very limited definition of “logic.” Construed properly, we suggest, logical reasoning may be understood as the basic framework underlying all forms of cognition, including those conventionally thought of as illogical and irrational.

“Only a small community has concentratedon general intelligence. No one has tried to make a thinking machine... The bottom line is that we really haven't progressed too far toward a truly intelligent machine. We have collections of dumb specialists in small domains; the true majesty of general intelligence still awaits our attack.... We have got to get back to the deepest questions of AI and general intelligence... ” –MarvinMinsky as interviewed in Hal's Legacy, edited by David Stork, 2000. Our goal in creating this edited volume has been to?ll an apparent gap in the scienti?c literature, by providing a coherent presentation of a body of contemporary research that, in spite of its integral importance, has hitherto kept a very low pro?le within the scienti?c and intellectual community. This body of work has not been given a name before; in this book we christen it “Arti?cial General Intelligence” (AGI). What distinguishes AGI work from run-of-the-mill “arti?cial intelligence” research is that it is explicitly focused on engineering general intelligence in the short term. We have been active researchers in the AGI?eld for many years, and it has been a pleasure to gather together papers from our colleagues working on related ideas from their own perspectives. In the Introduction we give a conceptual overview of the AGI?eld, and also summarize and interrelate the key ideas of the papers in the subsequent chapters.

Cybernetic pioneer Warren McCullough asked:'What is a man, that he may know a number; and what is a number, that a man may know it?'Thinking along much the same lines, my question here is:'What is a creative mind, that it might emerge from a complex system; and what is a complex system, that it might give rise to a creative mind?'Complexity science is a fashionable topic these days. My perspective on complexity, however, is a somewhat unusual one: I am interested in complex systems science principally as it reflects on abstract mathematical, computational models of mind. In my three previous books, The Structure of Intelligence, Evolving Mind, and Chaotic Logic, I have outlined a comprehensive complex-systems-theoretic theory of mind that I now call the psynet model. This book is a continuation of the research program presented in my previous books (and those books will be frequently referred to here, by the nicknames EM and CL). One might summarize the trajectory of thought spanning these four books as follows. SI formulated a philosophy and mathem- ics of mind, based on theoretical computer science and the concept of'pattern.'EM analyzed the theory of evolution by natural selection in similar terms, and used this computational theory of evolution to establish the evolutionary nature of thought.