Computers and Programming

Most books about ChatGPT explain the magic. This one shows you the math. Inside Large Language Models, Volume I takes a curious beginner from "what is an LLM" to a complete, trained GPT, with nothing more than high-school algebra, a working laptop, and a willingness to read carefully. Every formula is walked through by hand. Every line of code comes with a plain-English explanation. By the end you will have built, trained, and run your own transformer from scratch, and you will know exactly what is happening inside. No PhD or Data Science required. No prior machine learning needed. Just curiosity and a calculator.

Stop being a 'Syntax Coder' and start becoming a 'Diagnostic Architect' by mastering the hidden mental models of software failure. This book teaches you how to own every logical branch of your system and eliminate bugs before they even happen. Stop guessing and start diagnosing.

If you've ever wondered what the quantum computing stack actually looks like from top to bottom, this is the book.

如果惯性可以被编程会怎样？本书在 11 种编程语言中实现了 NKTg 定律 = f(x, v, m)，并通过真实 ESA 火星数据验证，误差仅为 0.208% —— 从 Python 到 Assembly，从人工智能到量子计算。

From the "original sin" of the stateless web to the looming threat of quantum-powered breaches, Something You Don't Know decodes the thousands of years of human ingenuity behind the login box. You will master modern engineering essentials like passkeys, Zero Trust architecture, and ML-KEM while learning to secure the next frontier: autonomous AI agents. It is the definitive guide for senior engineers who want to understand the physics of identity and build systems that are truly unshakeable.

Most developers treat Hibernate as a black box that turns objects into rows. This book opens the box, shows you exactly what happens inside, and teaches you how to make it work for you at scale.

Build a complete, production-grade microservices platform with Spring Boot 4 and Java 21, one chapter at a time.

Working with PySide6 should not depend on trial and error. This book replaces fragmented learning with a structured approach, combining in-depth explanations and dependable code examples that move you forward with confidence.

Exploring Java Libraries: A Developer’s Guide, Volume II is a hands-on guide to Java’s text-processing, desktop GUI, and accessibility libraries. Through practical examples, structured explanations, and real-world coding scenarios, it helps developers move beyond theory and master Java’s AWT, Swing, and java.text ecosystem.

Learn how to build Kubernetes Operators from scratch using Kubebuilder, step by step. You will create real controllers, work with CRDs, and understand how reconciliation works in practice. By the end, you’ll know how to design, test, and run your custom operator.

The Ruby book that never gets old — updated with every major release, free forever for everyone who buys it. Written by the author of the first Ruby book ever published in Brazil, and believed to be the first book worldwide to cover RubyLLM. Now in English for the first time.

### **Book Overview** * **Total Chapters:** 11 Chapters * **Structure:** 4 Sections * **Scope:** 40+ Key Topics * **Estimated Reading Time:** ~3 hours ### **Preface** * **Theme**: Knowledge is the most powerful defense in an age of invisible algorithmic systems. * **Target Audience**: A comprehensive guide for curious minds, including students, professionals, parents, and policymakers. * **Mission**: To empower readers to build a "digital fortress" around their data, identities, and values. ### **Section 1: The Foundations of the Fortress** * **Chapter 1: The Invisible Architect** * Explores how AI silently shapes daily digital life, from news feeds to medical treatments. * Includes a timeline of AI milestones from 1950 (Turing Test) to 2024 (drug discovery and climate modeling). * Discusses the "Black Box" problem and the lack of explainability in neural networks. * **Chapter 2: Algorithms vs. Ethics** * Debunks the myth of machine objectivity. * Analyzes sources of algorithmic bias: training data, feature selection, feedback loops, and aggregation. * Case studies: COMPAS (criminal justice), Amazon’s hiring tool, and facial recognition errors. * **Chapter 3: The Data Fuel** * Examines "Surveillance Capitalism" and how personal data is treated as the world's most valuable raw material. * Details the types of data collected: identity, behavioral, location, social, and inferred data. ### **Section 2: Inside the Walls: Security & Risks** * **Chapter 4: The Sentinel AI** * Analyzes AI in cybersecurity as both a "Guardian" (threat detection, automated response) and a "Threat" (AI-powered phishing, malware generation). * **Chapter 5: Deepfakes and Deception** * Explains Generative Adversarial Networks (GANs) and the death of "epistemic trust". * Highlights impacts: political manipulation, financial fraud, and the "Liar's Dividend". * **Chapter 6: Automated Warfare** * Discusses Lethal Autonomous Weapons Systems (LAWS) and the moral rupture of removing human accountability from the battlefield. ### **Section 3: The Human Connection** * **Chapter 7: AI and Human Rights** * Investigates digital mass surveillance, social credit systems, and facial recognition networks. * **Chapter 8: The Future of Work** * Addresses "automation anxiety" and the shift from replacing physical labor to replacing cognitive labor. * Strategies for an "AI-proof" career: empathy, leadership, and cross-domain expertise. * **Chapter 9: Ethical AI Frameworks** * Reviews global regulations: EU AI Act (2024), NIST Risk Management Framework, and Asilomar AI Principles. ### **Section 4: The Future Outlook** * **Chapter 10: Building Your Personal Fortress** * A practical, three-level action plan for digital security. * **Level 1 (Essential)**: Password managers, 2FA, and system updates. * **Level 2 (Enhanced)**: VPNs, privacy browsers, and search engine alternatives. * **Level 3 (Advanced)**: Signal for messaging, encrypted email (ProtonMail), and quarterly digital hygiene. * **Chapter 11: Toward a Symbiotic Future** * Moving beyond techno-optimism and techno-pessimism toward critical engagement. * Visions for AI in medicine, education, and climate governance guided by human values. ### **Final Word** * A closing reminder that the future of AI is determined by our choices as citizens, consumers, and humans.

跳过黑箱框架。用纯 Python 从零构建生产级 AI 编程智能体——云端或本地，用 pytest 测试，全部在一个文件中完成。

ブラックボックスのフレームワークは不要。純粋なPythonでプロダクションレベルのAIコーディングエージェントをゼロから構築。クラウドでもローカルでも、pytestでテスト済み、すべて1つのファイルに収まります。