Artificial Intelligence

What happens when artificial intelligence surpasses human intelligence across nearly every field? Super Intelligence explores how such systems could emerge, what they might be capable of and how they could reshape science, society and civilization. Grounded in research and technical evidence, this book cuts through the hype to examine what super intelligence could really mean.

机器人真正学会做饭，不是因为工程师写完了每一步，而是因为它能从身体经验、失败与恢复中形成自己的手艺。

为什么参数不大的模型，把信息放对地方就能反超更大的模型？本书以"压缩"为主线，把大模型的表示、泛化、推理、RAG 与智能体统一成一道信息管理题：什么该压、什么不能丢、什么该外置、放在哪里、何时取回。18 章、190 张原创图解，从熵一路讲到世界模型。

A Comprehensive Engineering Guide to Autonomous Agent Architectures, Multi-Agent Systems, Memory, Tool Execution, Reliability, Observability, and Production DeploymentAutonomous AI agents represent a fundamental shift from conventional conversational applications toward software systems capable of executing multi-step tasks, interacting with external tools, maintaining persistent state, coordinating specialized components, and adapting their behavior to changing conditions. Building such systems requires considerably more than connecting a language model to a prompt. It demands a disciplined approach to execution control, memory architecture, workflow orchestration, security, evaluation, and production infrastructure.Mastering AI Agents: Hands-On Production Code is a practical, implementation-focused engineering reference to designing, building, and deploying autonomous AI agent systems. Across 38 chapters, it progresses from low-level LLM runtime primitives and a zero-dependency Python agent loop to cognitive architectures, persistent memory, stateful workflows, multi-agent coordination, secure tool execution, production observability, and enterprise deployment.

Get more from Claude Sonnet 5.5 with practical prompting techniques that actually work. This guide explores instruction design, effort control, tool use, structured outputs and agentic workflows, with clear distinctions between documented behavior and practical experience. Built for developers, prompt engineers and advanced users.

What if you could build an AI that writes just like you? In Building Your LLM Twin, you'll follow a hands-on journey from raw writing data to a fully deployed AI that captures your unique voice. Learn to build, fine-tune and scale real-world LLM systems with practical code, proven techniques and the tools to take your project from concept to production.

Unlock the full potential of large language models with RAG. This book takes you from core concepts to production-ready systems, exploring everything from embeddings and search to evaluation and security. With clear explanations, runnable code and practical insights, you'll learn how to build reliable AI systems grounded in the knowledge that matters.

Que una IA tenga razón no significa que tenga permiso para actuar. Una guía práctica para diseñar sistemas de IA donde capacidad, evidencia, autorización y ejecución permanecen separadas antes de producir una consecuencia real.

Answered sounds like it worked. Twice, it didn't. This book measures exactly where six seconds of silence goes in a real phone call, and does not stop measuring for the next thirty-four chapters.

AI can analyze the data. But who decides what the data means—and what to do next?Modern organizations have more information than ever, yet making good decisions remains difficult.AI-Powered Smart Decision Making shows how to combine AI, data, analytics, and human judgment to turn information into insight and insight into action.Discover a practical framework for making better decisions across strategy, marketing, sales, operations, finance, risk, and beyond.AI is not the decision. AI improves the decision process. Table of ContentsIntroduction—The New Era of AI-Powered Decision MakingChapter 1 — The Foundations of Better Business DecisionsChapter 2 — From Intuition to Data-Driven Decision MakingChapter 3 — Understanding Data for Better DecisionsChapter 4 — Business Analytics: Turning Data into InsightChapter 5 — How AI Changes Business Decision MakingChapter 6 — Building an AI-Powered Decision FrameworkChapter 7 — Asking the Right Questions: AI, Data & Decision ProblemsChapter 8 — Predictive Decision MakingChapter 9 — Prescriptive Analytics and Decision OptimizationChapter 10 — AI for Strategic Business DecisionsChapter 11 — AI for Marketing and Customer DecisionsChapter 12 — AI for Sales, Operations and Supply ChainChapter 13 — AI for Financial and Risk DecisionsChapter 14 — Human + AI: The New Decision-Making PartnershipChapter 15 — Bias, Uncertainty and the Limits of AI DecisionsChapter 16 — Trustworthy, Responsible and Explainable AI DecisionsChapter 17 — Measuring Decision Quality and Business ImpactChapter 18 — Building an AI-Powered Decision CultureChapter 19 — Designing an AI-Powered Decision SystemChapter 20 — The Future of Smart Decision MakingConclusion — From Data to Better DecisionsDisclaimer

AI can decide. That does not mean it is authorized to act. Governance Before Decision examines the missing control layer between intelligent systems and real-world consequences — where authority, scope, verification, and execution must meet.

You don't need to code AI to understand its impact.Thinking Beyond Code: A Human’s Guide to Artificial Intelligence takes readers beyond algorithms and programming to explore the questions that matter most in an AI-powered world.How do machines learn? Can AI really think? Can machines be creative? What happens to jobs when automation expands? Who is responsible when an AI system makes a decision? Can AI-generated content change our understanding of truth? And what might happen if increasingly capable AI systems become part of everyday human life?From machine learning and neural networks to creativity, ethics, employment, deepfakes, AGI, and human-AI collaboration, this book offers an accessible journey through the technology and the human questions surrounding it.Understand the technology. Question the assumptions. Think beyond the code.

Discover the algorithms behind intelligent machines.Artificial Intelligence: Algorithms and Applications Unveiled takes readers from the fundamental concepts of AI to the algorithms and applications shaping modern technology. Explore machine learning, neural networks, deep learning, natural language processing, computer vision, robotics, healthcare, finance, business intelligence, and more.Designed to connect theory with practical understanding, the book explains how AI algorithms work, where they can be applied, and what challenges must be considered when building intelligent systems.From learning algorithms to responsible AI, this book provides a structured pathway for students, developers, researchers, educators, and technology professionals who want to understand the rapidly evolving world of Artificial Intelligence.Learn the algorithms. Understand the applications. Think intelligently about AI.

What happens when AI moves beyond answering questions and begins to pursue goals?Agentic AI: The Rise of Autonomous, Goal-Driven Intelligence explores the emerging world of intelligent systems that can perceive, reason, plan, learn, collaborate, and act within defined environments.From the foundations of autonomous agents and multi-agent systems to robotics, finance, logistics, security, ethics, and future research, this book provides a structured journey through the rapidly evolving landscape of Agentic AI.Discover how goal-driven intelligence works, how autonomous agents make decisions, how multiple agents collaborate, and why safety, trust, accountability, and human oversight are essential to the future of autonomous systems.Understand the agents. Explore the architectures. Examine the applications. Think about the future.

Master AI/ML System Design with a Structured Interview FrameworkLearn how to approach complex ML system design interviews using a 20-step framework, architecture blueprints, real-world case studies, scalability strategies, data and model pipelines, deployment patterns, monitoring, and interview-ready templates.