Generative AI Basic Concepts
When I first started learning about Generative AI, I remember feeling overwhelmed by the sheer number of new concepts. Like many others, I found myself wondering, 'What exactly is a transformer architecture, and how does it relate to GPT?' If you've had similar questions, you're not alone!
In my video 'Generative AI Basic Concepts,' I break down these essential ideas into easily digestible pieces. I share my own journey of understanding, starting with the fundamental building blocks like tokens and large language models. I also dive into the game-changing transformer architecture, which is a bit like a superhighway for processing and understanding language.
By the end of the video, you'll have a solid grasp of key concepts such as Generative Pre-trained Transformers (GPT), Supervised Fine-Tuning (SFT), and Reinforced Learning with Human Feedback (RLHF). I'll also demystify Vector Databases and Diffusion Models, empowering you with the knowledge to confidently navigate the exciting world of AI.
Join me on this learning journey, and together, we'll unlock the potential of Generative AI!
00:00 Who am I?
00:21 Introduction
01:15 How does LLM work?
03:11 What are Tokens?
05:28 What is the 2-gram?
07:26 What is the 3-gram?
08:50 What is the 4-gram?
12:57 Attention is all you need - Transformer
18:10 Generating Language
20:12 What about Creativity - Temperature
22:14 How do you steer? Supervised Fine Tuning
25:10 Reinforcement Learning with Human Feedback (RLHF)
26:48 Why did we have a jump in performance? Scale and Speed
28:51 What is a Vector Database?
36:18 What are Diffusion Models?
47:58 Questions
49:37 Outro
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