What a Large Language Model Really Is — From Turing to ChatGPT [AI Stack 01]
What is a large language model, really? Episode one of The AI Stack tells the whole story: from Alan Turing's 1950 question and the 1956 birth of the term "artificial intelligence," through the rule-writing era and the AI winters, to the machine-learning age of predictive analytics, and finally to the transformer and the large language models behind ChatGPT, Claude, and Gemini. We explain the new dimension LLMs added to AI, and how trained parameters make a model context-aware. No hype, just the real arc of how AI learned to talk. Subscribe and follow the series from the start.

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Every AI Model Explained in 19 Minutes
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Yann LeCun's $1B Bet Against LLMs [Part 1]
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How Does Tokenization Work? (And Why It Drives Your AI Cost) — [AI Stack 02]

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The Secret Race to Create GPT 5.6 – Who Will Shape AI’s Future?

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MIT Just Revealed the AI Bubble's Fatal Flaw
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How Do Vector Embeddings Work? (Turning Words Into Meaning) — [AI Stack 03]

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How To Use Claude Better Than 99% Of People

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LLMs Don't Need More Parameters. They Need Loops.

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We just figured out how AI actually works (J-Space)

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Why AI Has Failed to Take Your Job Since 1976

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Only Video That Will Make You BETTER at MATH - 100%

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How To Become Dangerously Self-Educated (with AI)

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China Is About To Pop The AI Bubble

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Complete Agentic AI Course - AI Agents, RAG, Embeddings, Architectures, Framework, VectorDB & Memory

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FULL Claude Tutorial for Beginners in 2026! (Become a PRO!)

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How AI agents & Claude skills work (Clearly Explained)

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The AI Skills Nobody is Teaching (And Everyone Needs) | AI Expert Ethan Mollick

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I speak 12 languages - copy my 30 min learning routine

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From Child Prodigy to Winning Fields Medal, Nobel of Math

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