Prompt Engineering Series: Module 2 AI Token System

Understanding AI’s Token System | GPT Models Input/Output Explained Ever wondered how AI like ChatGPT, GPT-4, and GPT-3.5 process your prompts? 🤔 In this video, we break down the AI token system — the building blocks that power large language models. 🚀 Ready to go from random to remarkable? Watch now, then join the full AI Masterclass to become a prompt engineering pro. 🎯 Enroll here with limited time coupon added → https://www.udemy.com/course/ai-course-chatgpt-prompt-engineering/?couponCode=2F572C52DB3F40308F20 If coupon expired then reach out at [email protected] for active coupon. 🎓 What You’ll Learn: ✅ What tokens are and how GPT models use them ✅ How prompts and responses consume tokens ✅ Token limits across different models (GPT-3.5, GPT-4 Turbo, GPT-4o, GPT-4o Mini) ✅ Why long prompts sometimes get cut off or ignored ✅ A simple analogy to make tokens easy to understand 🧠 Key Analogy: Think of tokens as pages in a notebook. Each AI model has a fixed number of pages to “remember” your input and generate a response. Exceed the limit, and some pages (information) get dropped. 🔥 Why Watch This Video? If you’re into AI, prompt engineering, or building with LLMs, understanding tokens is crucial. Knowing how token limits work helps you: Write smarter prompts ✍️ Avoid wasted API calls 💸 and Get better responses from AI 🤖 👉 Subscribe for more tutorials on AI, ChatGPT, and Prompt Engineering 👉 Drop your questions in the comments, and we’ll cover them in future videos! #ChatGPT #GPT4 #AIExplained #TokenSystem #PromptEngineering