Transformers, explained: Understand the model behind ChatGPT

🚀 Learn AI Prompt Engineering: https://bit.ly/3v8O4Vt In this technical overview, we dissect the architecture of Generative Pre-trained Transformer (GPT) models, drawing parallels between artificial neural networks and the human brain. From the foundational GPT-1 to the advanced GPT-4, we explore the evolution of GPT models, focusing on their learning processes, the significance of data in training, and the revolutionary Transformer architecture. This video is designed for curious non-technical people looking to understand the complexities of GPT models in a way that's easy to understand. 🔗 SOCIAL LINKS: 🌐 Website/Blog: https://www.futurise.com/ 🐦 Twitter/X: https://twitter.com/JoinFuturise 🔗 LinkedIn: https://www.linkedin.com/school/futurisealumni 📘 Facebook: https://www.facebook.com/profile.php?id=61554991705154 📣 Subscribe: https://www.youtube.com/@leonpetrou?sub_confirmation=1 ⏰ Timestamps: 0:00 - Intro 0:27 - The Importance of Modeling The Human Brain 1:10 - Basics of Artificial Neural Networks (ANNs) 2:26 - Overview of GPT Models Evolution 3:34 - Training Large Language Models 7:05 - Transformer Architecture 7:45 - Understanding Tokenization 10:19 - Explaining Token Embeddings 17:03 - Deep Dive into Self-Attention Mechanism 18:53 - Multiheaded Self-Attention Explained 19:55 - Predicting the Next Word: The Process 22:33 - De-Tokenization: Converting Token IDs Back to Words #llm #ml #chatgpt #nvidia #elearning #futurise #promptengineering #futureofwork #leonpetrou #anthropic #claude #claude3 #gemini #openai #transformers #techinsights