Series · Part 2 of 21
Foundation
Transformers — The Architecture That Changed Everything
Every major AI — GPT, Claude, Gemini, Llama — runs on the Transformer. Here's how it works, stage by stage, with live visualizations.
In 2017, a Google paper called Attention Is All You Need described an architecture that would replace everything before it. GPT, Claude, Gemini, Llama — they all run on this.
The key insight: instead of processing words one at a time (slow, forgetful), attention lets every token relate to every other token simultaneously. Parallelizable, scalable, and the reason modern AI is possible.
Next up: Part 3 covers how AI actually learns — training, sampling, and why the same prompt doesn’t always give the same answer.
AI Demystified · 16 of 21 published
- 0 Grounding 5 Mental Models You Need Before Diving Into AI
- 1 Foundation What Happens When You Ask AI Something?
- 2 Foundation Transformers — The Architecture That Changed Everything
- 3 Foundation How AI Learns, Thinks, and Decides
- 4 Foundation How AI Reads Your Words
- 5 Foundation Why AI Forgets
- 6 Foundation Why AI Lies (And Doesn't Know It)
- 7 Foundation What AI Cannot Do
- 8 Foundation How AI Reasons (And Why It Sometimes Breaks)
- 9 Practice Prompt Engineering — How to Talk to AI
- 10 Practice Embeddings & Vector Databases — The Memory Layer of AI
- 11 Practice RAG Explained — How AI Knows What You Didn't Train It On
- 12 Practice Fine-tuning vs. Prompting — When to Use Which
- 13 Practice Do You Really Need GPT-4?
- 14 Practice Latency, Tokens, and Cost — The Physics of AI Products
- 15 Practice How Do You Know AI Is Actually Working?
- 16 Hands-On Coding Setup — Your AI Development Environment soon
- 17 Hands-On MCP Tool Calling — How AI Uses Tools soon
- 18 Hands-On AI Agents — Beyond Chatbots soon
- 19 Hands-On Build Your First Real AI App soon
- 20 Hands-On Token Optimization — Spend Less, Get More soon
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