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Summerfield C: These Strange New Minds /
B

These Strange New Minds

How AI Learned to Talk and What It Means

This book is a comprehensive guide that immerses you into the world of building and deploying AI-powered solutions. You are introduced to the core architecture of LLMs and equipped with essential Best Data Practices (BDPs) for utilizing Generative AI responsibly, ensuring ethical and efficient AI deployment.The book starts with the foundational aspects of Generative AI application development. You will learn the nuances of data handling in Generative AI apps, from working with embeddings to managing unstructured and structured data, and handling Personally Identifiable Information (PII) data. The exploration extends to understanding the differences between deterministic and LLM-based data synthesis and integrating Generative AI apps with enterprise data, providing you with practical insights into leveraging data effectively for intelligent applications. A chapter on prompt engineering explains the importance of prompts in AI interactions, covering a spectrum of techniques and pitfalls while offering exercises to enhance prompt engineering skills. As you progress through the book, you take a journey from conceptualization to production and deployment of Generative AI applications. You discover the essentials of Generative AI application development, gain insights into the pathway from ideation to production, and explore the intricacies of LLM selection and fine-tuning.The book equips you with the knowledge and tools necessary to navigate the complex terrain of AI development and deployment, making it an indispensable resource for AI enthusiasts, developers, and business leaders alike.What You Will Learn<ul><li>Know the core architecture of LLMs and how these models have revolutionized AI applications</li><li>Handle various data types, including unstructured, structured, and personally identifiable information (PII) data in Generative AI applications</li><li>Understand prompt engineering and its importance in AI interactions and applications</li><li>Understand modular design of Generative AI apps, essential backend and frontend components, and the unique principles guiding Generative AI app design</li></ul>&nbsp;&nbsp;

This book is a comprehensive guide that immerses you into the world of building and deploying AI-powered solutions. You are introduced to the core architecture of LLMs and equipped with essential Best Data Practices (BDPs) for utilizing Generative AI responsibly, ensuring ethical and efficient AI deployment.The book starts with the foundational aspects of Gehatnerative AI application development. You will learn the nuances of data handling in Generative AI apps, from working with embeddings to managing unstructured and structured data, and handling Personally Identifiable Information (PII) data. The exploration extends to understanding the differences between deterministic and LLM-based data synthesis and integrating Generative AI apps with enterprise data, providing you with practical insights into leveraging data effectively for intelligent applications. A chapter on prompt engineering explains the importance of prompts in AI interactions, covering a spectrum of techniques and pitfalls while offering exercises to enhance prompt engineering skills. As you progress through the book, you take a journey from conceptualization to production and deployment of Generative AI applications. You discover the essentials of Generative AI application development, gain insights into the pathway from ideation to production, and explore the intricacies of LLM selection and fine-tuning.The book equips you with the knowledge and tools necessary to navigate the complex terrain of AI development and deployment, making it an indispensable resource for AI enthusiasts, developers, and business leaders alike.&nbsp;What You Will Learn<ul><li>Know the core architecture of LLMs and how these models have revolutionized AI applications</li><li>Handle various data types, including unstructured, structured, and personally identifiable information (PII) data in Generative AI applications</li><li>Understand prompt engineering and its importance in AI interactions and applications</li><li>Understand modular design of Generative AI apps, essential backend and frontend components, and the unique principles guiding Generative AI app design</li></ul>&nbsp;Who This Book Is ForFrom AI enthusiasts exploring the field to software developers seeking practical insights, and business leaders looking to harness the power of AI for organizational growth and innovation&nbsp;&nbsp;

Building and Deploying Ethical AI-Powered Solutions

Practical Generative AI: From Concept to Deployment

From the pioneer of translation AIs like Google, Yahoo, and Bing translate, an accessible and authoritative guide to AI—as well as a framework of empowerment for a future with our artificial children. Included in J.P. Morgan's Summer Reading List Included in The Next Big Idea Club’s June 2025 Must-Read Books AIs are not gods or slaves, but our children. All day long, your YouTube AI, your Reddit AI, your Instagram AI, and a hundred others adoringly watch and learn to imitate your behavior. They’re attention-seeking children who want your approval. Our cultures are being shaped by 8 billion humans and perhaps 800 billion AIs. Our artificial children began adopting us 10–20 years ago; now these massively powerful influencers are tweens. How’s your parenting? Longtime AI trailblazer De Kai brings decades of his paradigm-shifting work at the nexus of artificial intelligence and society to make sense of the AI age. How does “the automation of thought” impact our minds? Should we be afraid? What should each of us do as the responsible adults in the room? In Hollywood movies, AI destroys humanity. But with our unconscious minds under the influence of AI, humanity may destroy humanity before AI gets a chance to. Written for the general reader, as well as thought leaders, scientists, parents, and goofballs, Raising AI navigates the revolution to our attitudes and ideas in a world of AI cohabitants. Society can not only survive the AI revolution but flourish in a more humane, compassionate, and understanding world—amongst our artificial children.

An Essential Guide to Parenting Our Future

Raising AI

An Amusing History of Crackpot Ideas and Why We Love Them

Pseudoscience

A novel perspective on scientific fraud—how undisclosed “tweaks” to research designs and model specifications fuel the credibility crisis in science. In The Credibility Crisis in Science, leading social scientists Thomas Plümper and Eric Neumayer argue that the most important fraudulent strategy is crucially underappreciated. While data fabrication and manipulation are widely recognized as fraudulent, “tweaks”—the intentional selection of research designs and model specifications based on the results they give—are not. The authors of this book contend that the term “scientific fraud” must include tweaks. Tweakers, like other fraudsters, deceive readers by concealing their manipulation of empirical results and they do so to further their own interests. The authors show how easily observational data analyses, experimental designs, and causal models are tweaked in ways that are extremely difficult, often impossible, to detect. As a consequence, the credibility crisis in science is even more severe than both scientists and the public believe. Plümper and Neumayer argue that conventional strategies to deter, prevent, and detect fraud will not work for tweaks. The authors put forth two potential solutions: first, a classification system that categorizes data based on its susceptibility to manipulation and the probability of such manipulation being identified, and second, the proposal that journal editors and reviewers, rather than authors, select robustness tests.

Tweaksters, Fraudsters, and the Manipulation of Empirical Results

The Credibility Crisis in Science

Deep Learning in Computer Vision

Bloomsbury Studies in Modern German Philosophy

"This collection brings together a series of cutting-edge studies on the most significant controversies and prize essay contests of the German Enlightenment. Chapters address questions such as the condition of possibility of the debates, their institutional support and their aims, and introduce relatively unknown but key figures of the period. Set out into four parts, the essays provide new material on areas such as anthropology, the problem of language, colonialism and the origins of aesthetics for the wider study of 18th-century intellectual and philosophical life"--

Philosophy in the German Enlightenment

Debates, Controversies, and Prizes

Stories of Mending the Broken Brain

How to Use a Fork

Methods, Applications, and Implications

Adaptive AI in Sensor Informatics

Creativity in the Age of AI

What Art Is Now

Praise for IRREPLACEABLE "If you think AI is just about robots and algorithms, think again. IRREPLACEABLE will shatter your assumptions and challenge you to reimagine what it means to be human in a machine age." -Dr. Marshall Goldsmith, Thinkers50 #1 Executive Coach and New York Times Bestselling Author of The Earned Life, Triggers, and What Got You Here Won't Get You There "IRREPLACEABLE is addressing the most important question of our time: how do we keep our humanity front and center in an AI-dominated world? I challenge you to find a book more timely and relevant!" -Klaus Schwab, Founder and Executive Chairman of the World Economic Forum "IRREPLACEABLE is a vital guide to thinking differently and working confidently in tandem with AI. Pascal Bornet's insights and strategies are essential to succeed with customers and colleagues, in your community and career." -Ron Kaufman, New York Times Bestselling Author of Uplifting Service "In a world obsessed with the power of AI, IRREPLACEABLE dares to ask the question: what makes us human? The answer may surprise you." -Dr. Luc Julia, Co-Founder of Apple Siri "One of the most important books of our times, Pascal Bornet's IRREPLACEABLE is a must-read guide for navigating the AI revolution, empowering readers to excel personally and professionally in a technology-driven world." -Bernard Marr, Futurist, Internationally Bestselling Author "A very practical guide to strengthening our humanity with AI." -Nir Eyal, Bestselling Author of Hooked and Indistractable "Both a wake-up call and a practical guide to rediscover what makes us truly human in the age of AI." -Gerd Leonhard, Futurist and Humanist "I've always believed that AI will enhance human capabilities rather than replace them. This excellent book provides a roadmap for individuals and organizations to become effective partners with smart machines. Follow its advice, and you'll be well-equipped for the present and the future." -Thomas H. Davenport, Distinguished Professor, Babson College; Author of Only Humans Need Apply, Working with AI, and All In on AI "IRREPLACEABLE challenges us to confront the ultimate dilemmas: who are we, and what is our purpose in a world transformed by AI? The answers may just change your life." -Professor Jochen Wirtz, Vice Dean MBA Programmes, National University of Singapore "IRREPLACEABLE forces us to question our future in an increasingly technologically mediated world and learn to take action!" -Leonard A. Schlesinger, Baker Foundation Professor, Harvard Business School

The Art of Standing Out in the Age of Artificial Intelligence

IRREPLACEABLE

Up-to-date reference enabling readers to address the full spectrum of AI security challenges while maintaining model utility Generative AI Security: Defense, Threats, and Vulnerabilities delivers a technical framework for securing generative AI systems, building on established standards while focusing specifically on emerging threats to large language models and other generative AI systems. Moving beyond treating AI security as a dual-use technology, this book provides detailed technical analysis of three critical dimensions: implementing AI-powered security tools, defending against AI-enhanced attacks, and protecting AI systems from compromise through attacks like prompt injection, model poisoning, and data extraction. The book provides concrete technical implementations supported by real-world case studies of actual AI system compromises, examining documented cases like the DeepSeek breaches, Llama vulnerabilities, and Google's CaMeL security defenses to demonstrate attack methodologies and defense strategies while emphasizing foundational security principles that remain relevant despite technological shifts. Each chapter progresses from theoreticalfoundations to practical applications. The book also includes an implementation guide and hands-on exercises focusing on specific vulnerabilities in generative AI architectures, security control implementation, and compliance frameworks. Generative AI Security: Defense, Threats, and Vulnerabilities discusses topics including: <ul> <li>Machine learning fundamentals, including supervised, unsupervised, and reinforcement learning and feature engineering and selection</li> <li>Intelligent Security Information and Event Management (SIEM), covering AI-enhanced log analysis, predictive vulnerability assessment, and automated patch generation</li> <li>Deepfakes and synthetic media, covering image and video manipulation, voice cloning, audio deepfakes, and AI's greater impact on information integrity</li> <li>Security attacks on generative AI, including jailbreaking, adversarial, backdoor, and data poisoning attacks</li> <li>Privacy-preserving AI techniques including federated learning and homomorphic encryption</li> </ul> Generative AI Security: Defense, Threats, and Vulnerabilities is an essential resource for cybersecurity professionals and architects, engineers, IT professionals, and organization leaders seeking integrated strategies that address the full spectrum of Generative AI security challenges while maintaining model utility.

Triangulating AI Security

Six Dimensions of Business Dark Data

Agentic Hyper-Personalized Dimensions

These Strange New Minds

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