Who Is Alexander Grothendieck? Part 1: Anarchy 1

Separate the AI facts from the AI fiction, and discover how you can best put these tools to work in your organization. It’s hard to say what’s bigger: AI’s tremendous promise, or all the hype surrounding it. Is it just another flash in the pan—or is AI going to change the way we all work? In AI Reality and Illusion, AI professor and entrepreneur Dr. Akli Adjaoute shares his 30 years of experience in a vital guide to the whole AI field. It lays out a pragmatic blueprint that every leader needs to drive innovation with artificial intelligence and shape the future of their business. Inside AI Reality and Illusion you’ll learn how to: Distinguish between AI hype and reality Identify the capabilities and limitations of AI systems Gain insight into diverse AI techniques and methodologies Understand successful and failed uses of AI in business Manage AI projects effectively AI Reality and Illusion tours every leading technique of AI and machine learning, showing you how they work, and how you can incorporate them into your business. There’s no hype here—you’ll get the kind of grounded, evidence-based insights that are vital for making strategic decisions about AI. Accessible, non-technical language and real-world use cases help you develop a practical AI literacy so you can start using these tools to their full potential. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the book AI Reality and Illusion is a comprehensive—but accessible—overview of AI for leaders and decision makers that sifts the truth from the myths for multiple different AI techniques. Inside, you’ll explore everything from traditional expert systems to modern deep learning including Large Language Models (LLMs) and generative AI. Throughout, Dr. Adjaoute shares his real-world experience applying AI to mission-critical applications, letting you learn from both his successes and failures. You’ll learn how to identify strategic opportunities with AI, manage an AI adoption, and plan your investment strategies with consideration to AI’s future advancements. About the reader For anyone seeking grounded, hype-free insights into AI’s capabilities. No technological expertise required. About the author Dr. Akli Adjaoute is the founder of Exponion, a venture capital firm that provides cutting-edge startup companies with financial resources and expertise. Prior to Exponion, he was the founder and CEO of Brighterion, which was acquired in 2017 by Mastercard. Brighterion provides enterprise AI applications for payment service providers and financial institutions. Additionally, Dr. Adjaoute founded and led Conception Intelligence Artificielle, a company focused on AI technology. Alongside his entrepreneurial pursuits, he has shared his real-world AI experience as an adjunct professor in both France and the USA. Dr. Adjaoute has been awarded 28 patents with over 1800 citations. Inside AI Praise for Inside AI brief contents contents foreword preface acknowledgments about the book Who should read this book? How this book is organized liveBook discussion forum about the author about the cover illustration 1 The rise of machine intelligence 1.1 What is artificial intelligence? 1.2 The AI revolution 1.3 Error-prone intelligence 1.4 Chatbots 1.5 Looking ahead Summary 2 AI mastery: Essential techniques, Part 1 2.1 Expert systems 2.2 Business rules management system 2.3 Case-based reasoning 2.4 Fuzzy logic 2.5 Genetic algorithms Summary 3 AI mastery: Essential techniques, Part 2 3.1 Data mining 3.2 Decision trees for fraud prevention 3.3 Artificial neural networks 3.4 Deep learning 3.4.1 The benefits of deep learning 3.4.2 Limitations of deep learning 3.5 Bayesian networks 3.6 Unsupervised learning 3.7 So, what is artificial intelligence? Summary 4 Smart agent technology 4.1 Principles of smart agents 4.1.1 Adaptability: The true mark of intelligence 4.1.2 Smart agent language Summary 5 Generative AI and large language models 5.1 Generative artificial intelligence 5.2 Large language models 5.3 ChatGPT 5.3.1 How ChatGPT creates human-like text 5.3.2 ChatGPT hallucination 5.4 Bard 5.5 Humans vs. LLMs 5.6 AI does not understand 5.7 Benefits of LLMs 5.8 LLM limits 5.9 Generative AI and intellectual property 5.10 Risks of generative AI 5.11 LLMs and the Illusion of Understanding Summary 6 Human vs. machine 6.1 The human brain 6.1.1 Thoughts 6.1.2 Memory 6.1.3 The subconscious mind 6.1.4 Common sense 6.1.5 Curiosity 6.1.6 Imagination 6.1.7 Creativity 6.1.8 Intuition 6.1.9 Analogy 6.2 Human vision vs. computer vision 6.2.1 AI and COVID 6.2.2 Image reasoning Summary 7 AI doesn’t turn data into intelligence 7.1 Machines defeating world champions 7.2 Lack of generalization Summary 8 AI doesn’t threaten our jobs 8.1 Are simple human tasks easy to automate? Summary 9 Technological singularity is absurd 9.1 The genesis of technological singularity 9.2 The truth about the evolution of robotics 9.3 Merging human with machine? 9.4 Science fiction vs. reality Summary 10 Learning from successful and failed applications of AI 10.1 AI successes 10.2 AI misuse 10.3 AI failures 10.4 How to set your AI project up for success 10.4.1 Data: The lifeblood of AI 10.4.2 The realistic AI perspective 10.4.3 The importance of planning 10.4.4 Risk mitigation 10.4.5 Collaboration and expertise 10.5 AI model lifecycle management 10.5.1 Data preparation 10.5.2 Behavior analysis 10.5.3 Data transformation 10.5.4 Model creation 10.5.5 Live production 10.5.6 Data storage 10.5.7 Notifications 10.5.8 Back-office review 10.5.9 Adaptive learning 10.5.10 Administration 10.5.11 Remark on AI platforms 10.6 Guiding principles for successful AI projects Summary 11 Next-generation AI 11.1 Data flexibility 11.2 Sampling 11.3 Elimination of irrelevant attributes 11.4 Data coherence 11.5 Lack of bias in data and algorithms 11.6 Feature engineering 11.7 Technique combination 11.8 Unsupervised learning 11.9 AI factory 11.10 Quality Assurance 11.11 Prediction reliability 11.12 Effective data storage and processing 11.13 Deployability and interoperability 11.14 Scalability 11.15 Resilience and robustness 11.16 Security 11.17 Explicability 11.18 Traceability and monitoring 11.19 Privacy 11.20 Temporal reasoning 11.21 Contextual reasoning 11.22 Causality inference 11.23 Analogical reasoning and transferability 11.24 Personalization 11.25 Sustainable AI 11.26 Adaptability 11.27 Human–machine collaboration Summary appendix A—Tracing the roots: From mechanical calculators to digital dreams A.1 Can machines think? appendix B—Algorithms and programming languages B.1 Algorithms B.2 Programming languages epilogue references Chapter 2 Chapter 3 Chapter 5 Chapter 6 Chapter 7 Chapter 8 Chapter 9 Chapter 10 Chapter 11 Appendix A Appendix B index A B C D E F G H I J K L M N O P Q R S T U V W X Z **Separate AI truth from AI hype, and learn how to put this powerful technology to work.** In __Inside AI__ AI professor and entrepreneur Dr. Akli Adjaoute puts AI in perspective, with informed insights from 30 years spent in the field. His book lays out a pragmatic blueprint that every leader can utilize to drive innovation with artificial intelligence. In __Inside AI__ you’ll learn how to: * Gain insight into diverse AI techniques and methodologies * Learn from both successful and failed AI applications * Identify the capabilities and limitations of AI systems * Understand successful and failed uses of AI in business * See where human cognition still exceeds AI * Bust common myths like AI’s threat to jobs and civilization * Manage AI projects effectively __Inside AI__ takes you on a journey through artificial intelligence, from AI’s origins in traditional expert systems all the way to deep learning and Large Language Models. There’s no hype here—you’ll get the grounded, evidence-based insights that are vital for making strategic decisions and preparing your business for the future. about the technology Artificial Intelligence enthusiasts promise everything from human-like collaboration on everyday tasks to the end of work as we know it. Is AI just a flash in the pan, or can it really transform how you do business? This intriguing book sifts through the hype and separates the truth from the myths, with clear advice on what AI can—and can’t—achieve. about the book __Inside AI__ provides a clear-headed overview of modern artificial intelligence, including the recent advances of Generative AI and Large Language Models. Its accessible and jargon-free explanations of leading AI techniques showcase how AI delivers tangible advantages to businesses. Both inspiring and practical, this book provides a proven framework for developing successful AI applications.