How AI Actually Understands Words? Tokens & Embeddings Explained | GenAI Ep 0x03 скачать в хорошем качестве

How AI Actually Understands Words? Tokens & Embeddings Explained | GenAI Ep 0x03

Welcome to Episode 0x03 of the LLM & Generative AI Series — where we uncover one of the most important concepts behind modern AI systems: Tokens and Embeddings. Large Language Models don’t read text like humans. Instead, they convert words into numbers and mathematical representations that machines can understand. In this episode, we break down how tokens and embeddings form the foundation of ChatGPT, GPT models, and modern GenAI applications. 🚀 What you’ll learn: ✅ What are Tokens in LLMs? ✅ How text gets split into tokens ✅ Token limits and context windows explained ✅ What are Embeddings? ✅ How AI converts meaning into vectors ✅ Why embeddings enable semantic search & RAG systems ✅ Real-world examples from GenAI applications By the end of this video, you’ll clearly understand how AI understands meaning, similarity, and context — a key step before learning RAG, vector databases, and AI agents. Perfect for developers, AI engineers, data professionals, and GenAI beginners. 👉 Follow the full series as we move toward building real-world AI systems. 🔎 Keywords tokens explained AI, embeddings explained, LLM tokens and embeddings, vector embeddings tutorial, how ChatGPT understands text, semantic embeddings, GenAI fundamentals. 🔥 Hashtags #GenerativeAI #LLM #Embeddings #ArtificialIntelligence #MachineLearning #GenAI #VectorDatabase #AIEngineering #ChatGPT #DeepLearning #LearnAI #AIForDevelopers