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Your data is correct. Your AI's answers are wrong. Here is why - and the fix. You connect a language model to a clean, normalised database and something strange happens: the facts are right, but the answers are wrong in a business sense. The model rejects a claim that a pending renewal should have saved, quotes a rule that expired last year, and cannot say which factory stops when a port closes. The cause is simple: we hand the model isolated rows and expect it to reconstruct the knowledge on its own. It cannot. AI-Native Knowledge Graphs is a hands-on course in eleven runnable lessons that...

In this insider’s look into the world’s biggest tech company, former CEO and SVP of Google share how they helped engineer a new strategy and philosophy to help them thrive—a perfect book for seasoned business employees and the tech curious. Today, Google is a global icon that regularly...

Your LLM is brilliant — until you ask it about YOUR data. It hallucinates. Its knowledge is frozen in the past. It has never seen your company's documents. Retrieval-Augmented Generation (RAG) is the architecture that fixes all three — and this book is the map that takes you from your first chunk to a fully agentic system. Architecting Knowledge is not another collection of scattered tutorials. It is a complete engineering curriculum: 34 concise chapters, 7 parts, one natural progression — why RAG exists, how a pipeline is anatomised, which building blocks to master, how to compose ...

Every engineer who has shipped a working AI demo knows the feeling. The chatbot runs cleanly on handpicked test data, the team celebrates, and someone posts a screenshot with fire emojis. Then Monday arrives — real users, real traffic, inputs that look nothing like the weekend test cases. Latency spikes. Token costs compound unexpectedly. Hallucinated answers reach paying customers. Logs reveal nothing useful when failures occur. There is no reliable signal that any change — a prompt tweak, a model swap, a chunk-size adjustment — actually made things better or worse. The gap between a...

The Internet just came out of the blue, people were a bit suspicious of what it really was about at first. No one had special interests in it to begin with. But now fast-forward that a few decades later, the internet has become an everyday necessity. Thanks to genius scientists like Tim Berners-Lee for creating the world wide web, and making the internet less techie. Since the web became more interactive and easier to use by the common folk, it grew like a mushroom and covered the entire globe in almost an instant. Almost everything nowadays happens online. Ask anyone who lives in a ...