How ChatGPT Actually Works: Tokens, Limits and Prompts

How ChatGPT actually works underneath — tokens, training, and why it fails the way it does. Not how to use it, but what's happening when you type.

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⏱️ Chapters:
0:00:00 Understanding AI and Machine Learning
0:08:16 Introduction to Generative AI and Chatbots
0:19:55 What Made ChatGPT Different
0:23:27 The Technique Behind ChatGPT
0:33:35 Comparing the Main AI Chatbots
0:38:14 Prompt Engineering Explained
0:43:57 The Concept of Tokens
0:55:38 A Toolkit for Writing Effective Prompts
1:04:50 Real-Life Applications
1:20:48 Limitations and Biases of ChatGPT
1:31:50 Should You Be Scared of AI?

📋 What's covered: the difference between AI and machine learning, how generative models produce text, the technique behind ChatGPT, how tokens work and why they govern cost and context, writing prompts that hold up, real applications across work, and where the model's limits and biases actually come from.

No prior knowledge required.

📅 Recorded earlier in ChatGPT's history. The chatbot comparison names tools that have since been renamed — Bard became Gemini, Bing AI became Copilot — and the capability limits discussed have moved. The fundamentals (how models generate text, how tokens work, where bias comes from) haven't changed.

ℹ️ This course is independent and is not affiliated with, endorsed by, or sponsored by OpenAI, Google, or Microsoft. For educational purposes only.

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