Generative AI Glossary: Essential Terms & Concepts Explained скачать в хорошем качестве

Generative AI Glossary: Essential Terms & Concepts Explained

Ever wonder how "magic" tools like ChatGPT and Midjourney actually work? In this video, we pull back the curtain on the world of Generative AI. Whether you're a tech enthusiast or just curious, this comprehensive glossary breaks down the most important terms and architectures in plain English. We’ll explore the "blueprints" of modern AI, including Transformers, Diffusion Models, and GANs. You’ll also learn the difference between Fine-tuning and RAG, the art of Prompt Engineering, and why Responsible AI is the most crucial piece of the puzzle. 🚀 What you’ll learn: The fundamental difference between generative and analytical AI. How the Attention Mechanism helps AI understand context. The "sculpting" process behind AI image generation. The "librarian" analogy for understanding AI training (RAG vs. Fine-tuning). Pro tips for Zero-shot and Few-shot prompting. 🕒 Timestamps: [00:00] Introduction to Generative AI [00:46] What is Generative AI? (Creating vs. Analyzing) [01:30] The Blueprints: Transformers & Attention Mechanism [02:14] Diffusion Models: How AI Images are Created [03:23] GANs (Generative Adversarial Networks) Explained [04:02] Training AI: Fine-tuning vs. RAG [04:58] Key Training Terms: Backpropagation, Epoch, & RLHF [05:31] Prompt Engineering: Zero-shot vs. Few-shot Prompting [06:20] Real-world AI: Vector Databases, Agents, & LLMOps [06:53] The Importance of Responsible AI & Ethics 💡 Subscribe to The Savvy Scholar for more deep dives into the technologies shaping our future! #GenerativeAI #AIGlossary #MachineLearning #ArtificialIntelligence #ChatGPT #DiffusionModels #TechExplained