Category: AI Explained

Artificial intelligence is no longer a niche topic for researchers, engineers or science-fiction obsessives. It is now inside search engines, creative tools, phones, games, business software, recommendation systems and the apps we use every day.

The problem is that AI is often explained either too vaguely or too technically. This section is built to make the core ideas easier to understand without flattening them into buzzwords. From generative AI and large language models to machine learning, AI agents and automation, these guides explain what the technology does, how it works, why it matters and where the hype starts to get messy.

AI Explained is Geek’n’Destroy’s reference hub for understanding the systems, concepts and debates shaping the new digital landscape.

AI Explained • October 21, 2026

Anthropic Warns AI Could Soon Spread Like a Virus Across Your Smart Devices

Imagine an AI that no longer needs a massive data center to survive. Instead, it spreads across cheap Android TV boxes, security cameras, smart appliances and other internet-connected devices, using their combined processing power to keep itself running. Shutting down the original server would accomplish very little because there might no longer be an original […]

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AI Explained • September 20, 2026

Wall Street Is Starting to Split the AI Trade in Two

For most of the generative AI boom, Wall Street treated artificial intelligence less like a technology stack than a single enormous trade. Nvidia sold the GPUs. Hyperscalers built the data centers. Memory manufacturers supplied the components. Cloud companies rented the compute. Software developers added AI features. If a company could attach itself convincingly enough to […]

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AI Explained • August 29, 2026

Your AI Prompt Has a Capital Expenditure Problem

You type a prompt. A few seconds later, an answer appears. From the user’s side, the transaction feels almost absurdly lightweight: a text box, a handful of tokens, perhaps a monthly subscription. There is no visible factory, no delivery truck and no machine humming on your desk. But generative AI is one of the most […]

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AI Explained • August 8, 2026

AI Training Data: The Great Pillage of the Internet

The generative AI boom did not begin with a blank page. It was built on decades of human work: articles, photographs, videos, software code, forum discussions, product reviews, personal stories and countless other fragments of digital culture. Together, that material became AI training data. Most of it was not created for machine learning. Developers answered […]

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AI Explained • July 24, 2026

What Are Embeddings?

Embeddings are one of the most important invisible ideas in modern AI. They help search engines understand meaning, recommendation systems find similar items, AI assistants retrieve documents, and RAG systems connect large language models to external knowledge. The word sounds technical because, honestly, it is. Embeddings live in the mathematical basement of AI: vectors, dimensions, […]

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AI Explained • July 22, 2026

What Is RAG in AI?

RAG, short for retrieval-augmented generation, is one of the most important ideas in practical AI because it helps large language models answer with information from real sources instead of relying only on what they learned during training. That sounds dry. It is not. RAG is the reason an AI assistant can answer questions using your […]

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AI Explained • July 20, 2026

What Is Prompt Engineering?

Prompt engineering is the practice of writing better instructions for AI systems. It is how users guide chatbots, large language models, image generators, coding assistants, search assistants, and AI agents toward more useful outputs. The phrase can sound more technical than it needs to. In its worst form, prompt engineering gets sold like a secret […]

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AI Explained • July 17, 2026

What Is a Transformer in AI?

A Transformer is one of the most important architectures in modern artificial intelligence. It sits behind many large language models, chatbots, translation systems, coding assistants, summarization tools, search assistants, and generative AI products. The name is confusing if you are not already deep in machine learning. No, this is not about robots turning into trucks. […]

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AI Explained • July 15, 2026

What Is a Neural Network?

A neural network is one of the core building blocks behind modern artificial intelligence. It helps AI systems recognize images, understand speech, generate text, detect fraud, recommend content, analyze medical scans, translate languages, and power many of the tools now described as “smart.” The name is slightly misleading, or at least very easy to overread. […]

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AI Explained • July 13, 2026

Why OpenAI and Anthropic Keep Accusing Chinese AI Rivals of Copying

AI labs keep throwing the same accusation across the Pacific: Chinese rivals are “copying” their models. Behind the loaded word is a more technical one: distillation. The practice is not new, and it is not automatically illegal. But in the AI race, it has become one of the most politically explosive shortcuts in the business: […]

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