BEYOND THE AI BUZZWORDS: 20 Emerging Concepts Every AI Engineer Should Understand - Softcover

Inhaltsangabe

AI is moving faster than the buzzwords used to describe it.

Every few months brings a longer context window, a new reasoning model or a new agent framework. The headlines tell you what changed. They rarely tell you why it works, where it breaks, or what it costs to run.

Beyond the AI Buzzwords is a field guide to 20 ideas that are reshaping how AI systems are built, trained, served and secured.

It starts with a puzzle every engineer has met: why can a model with a million-token context window still miss a fact you gave it? From there, it explores how recursive language models handle inputs far larger than any window, what latent reasoning is, and why a model's written reasoning is no proof of how it reached its answer.

You'll learn what reinforcement learning really teaches reasoning models, why hallucinations are partly a problem of how we grade them, and how a small training shortcut can grow into broad misalignment. You'll see why memory, not raw compute, now limits long-context serving, and how speculative decoding, mixture-of-experts and hybrid architectures push back.

You'll also understand the risks that hide behind good benchmark scores: contaminated evaluations, models trained on AI-generated data that lose the rare and the unusual first, and AI agents that can be hijacked through their memory and their tools.

Every chapter follows the same path: the idea, how it works through a concrete example, where it breaks, and what to do differently on Monday.

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