Artificial Intelligence

Prompting has more advice than evidence. This book measures it instead: a model reading apattern it has never seen, the same model failing at a task in one pass and solving itperfectly in four, a decoder that guarantees a format instead of improving the odds, and amodel that is 2.4% accurate while 78.6% confident. Six central claims are built from scratch and measured on a single CPU core. Everythingtaken from published research sits in a grey box marked "Not measured here" — so you neverhave to guess which is which.

AI governance is moving from principle to practice. This hands-on guide shows you how to build, implement and certify an ISO/IEC 42001 AI management system with confidence. From clause-by-clause guidance to practical templates, integration strategies and real-world scenarios, it turns a complex standard into a clear path from foundation to certification.

ਆਪਣੇ ਹੱਥੀਂ ਬਣਾਏ ਇੱਕ ਕੰਮ ਕਰਦੇ LLM ਰਾਹੀਂ AI ਵਾਂਗ ਸੋਚਣਾ ਸਿੱਖੋ। Cray Research ਦੀ ਪਰਖੀ ਅਤੇ ਪਰਵਾਨਿਤ ਸਿਸਟਮ ਸੋਚ ਨੂੰ ਆਧੁਨਿਕ AI 'ਤੇ ਲਾਗੂ ਕਰੋ। ਉਹ ਕੁਝ ਕਰ ਦਿਖਾਓ ਜਿਸਨੂੰ ਹੋਰ ਲੋਕ ਅਸੰਭਵ ਸਮਝਦੇ ਹਨ।

Tanulj meg úgy gondolkodni, mint egy mesterséges intelligencia, egy saját kezűleg felépített, működő nagy nyelvi modell (LLM) segítségével. Ez a Cray Research-nél csiszolt, gyakorlatban bevált rendszerszemléletű gondolkodást alkalmazza a modern MI-re. Érj el olyat, amit mások lehetetlennek tartanak.

Five certifications ask about the same twenty topics, and each one stops at a differentdepth. This book teaches the topic once, properly, then shows you exactly where each examstops — with 61 original practice questions where every wrong option is explained. Every number in it was measured. Every line of code was run. The code is included.

Domine a arquitetura de sistemas de IA autônomos. Um guia completo cobrindo motores de raciocínio, memória de longo prazo, orquestração multiagentes, otimização de custos e o Model Context Protocol (MCP). O livro definitivo para arquitetos e desenvolvedores.

面向智能体重度用户的实战可靠性手册：不教造智能体、不教提示词技巧、不做产品测评； 每天用智能体 2 小时以上、已配多个工具、需要一套可预算 / 可监控 / 可验收的运营方法的实践者；

The EU AI Act is changing the rules for anyone building, buying or using AI. This practical guide cuts through the legal complexity and shows what compliance actually requires. With clear explanations, real-world cases, templates and checklists, it gives leaders and teams the tools to turn regulation into workable AI governance.

The loop writes code and clears context. The commit log records MAX_RETRIES = 3, but the reason it's three vanished on Friday night. The artifact survived; the decision evaporated.The Loop That Remembers inverts the premise: memory isn't the sixth piece, it's what the loop exists to produce. Two graphs, a promoted lattice, bounded context, and an evaluator checking claims against edges.

Accountability cannot be delegated. Execution can. AI can act at a speed and scale that no person can review one decision at a time. The answer is not ceremonial human oversight. It is to establish who owns the workflow, what authority the system has, which limits are enforced and who can intervene when something goes wrong.Human Accountable for the Loop is a practical framework for doing that.

What if your AI didn’t just answer questions—but solved problems?Imagine an AI that doesn’t just chat—it plans, reasons, and takes action. An AI that can fetch data, run diagnostics, collaborate with other agents, and even handle your most tedious tasks—all while you focus on what matters.Google’s Agent Development Kit (ADK) makes this possible,

Go beyond using AI tools—learn to build AI solutions. AI Generalist Engineer is a practical guide for software engineers, architects, and technology leaders to master enterprise AI, AI agents, RAG, MCP, prompt engineering, orchestration, and modern AI architecture. Build the skills to design, integrate, and lead AI-powered systems with confidence.

Build smarter AI applications with Redis at the core. This practical guide shows you how to use vector search, RAG, semantic caching, agent memory and real-time inference to create fast, scalable systems. With runnable Python examples throughout, you’ll learn how to take AI projects from prototype to production.

当 AI 能替你写代码，真正的危险不是它写错，而是你以为它不会错。

An AI asked to build a network and its own tooling refused — no human had signed. Six weeks later the same machinery governed bare metal serving a 740B-parameter model, every step on a committed record. This book builds that lab from the ground up: the gate, the run records, the GitLab nervous system, the audit trail — AI doing real infrastructure work you can prove afterwards.