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Core Concepts

Master the fundamental ideas that power modern AI systems. Understand training data, model architectures, context windows, embeddings, and RAG—the building blocks that make AI work. Essential knowledge for anyone serious about AI.

What is RAG? A Beginner's Guide to Retrieval-Augmented Generation

Beginner

Understand RAG (Retrieval-Augmented Generation) in plain English. Learn how AI systems combine search with generation to give accurate, up-to-date answers.

10 min read
RAGretrievalgeneration

AI Model Architectures: A High-Level Overview

Intermediate

From transformers to CNNs to diffusion models—understand the different AI architectures and what they're good at.

7 min read
architecturestransformersmodels

Context Windows: How Much AI Can Remember

Intermediate

Context windows determine how much text an AI can process at once. Learn how they work, their limits, and how to work within them.

6 min read
contextmemorytokens

Embeddings: Turning Words into Math

Intermediate

Embeddings convert text into numbers that capture meaning. Essential for search, recommendations, and RAG systems.

7 min read
embeddingsvectorssemantic search

Multi-Modal AI: Beyond Text

Intermediate

Multi-modal AI processes multiple types of data—text, images, audio, video. Learn how these systems work and their applications.

6 min read
multimodalvisionaudio

Natural Language Processing: How AI Understands Text

Intermediate

NLP is how AI reads, understands, and generates human language. Learn the techniques behind chatbots, translation, and text analysis.

8 min read
NLPtext processinglanguage models

Training Data Quality: Garbage In, Garbage Out

Intermediate

AI quality depends on training data quality. Learn what makes good training data, common issues, and how to evaluate it.

7 min read
training datadata qualitybias