In this video, Raju Kandaswamy delves into the fascinating world of transformer architecture, shedding light on the critical role of self-attention in language models (LLM). Learn how self-attention drives LLMs, enabling them to grasp language patterns, understand grammar and semantics, and construct knowledge from input data. Uncover the origins of the transformer architecture from the groundbreaking paper "Attention is All You Need," published by Google. Interestingly, OpenAI reaped its benefits.

📚 Key Insights:

1. Self-Attention Unveiled: The Learning Mechanism
2. Transformer Architecture Origins: "Attention is All You Need"
3. Google vs. OpenAI: The Evolution of Language Models
4. The Impact of Self-Attention on Language Understanding

🔍 What You'll Discover:

1. The Crucial Role of Self-Attention in Language Understanding
2. Insights into the Transformer Architecture's Inner Workings
3. The Journey from Google's Paper to OpenAI's Success
4. Current Challenges and Developments in Language Models

🔥 Ready to demystify self-attention and explore the wonders of transformer architecture? Click play now and embark on a journey into the heart of language models! 🎥🚀 #NLP #AI #TechTalks #GenerativeAI