How I Finally Understood Self-Attention (With PyTorch)

Understand the core mechanism that powers modern AI: self-attention.In this video, I break down self-attention in large language models at three levels: conceptual, process-driven, and implementation in PyTorch.

Self-attention is the foundation of technologies like ChatGPT and GPT-4, and by the end of this tutorial, you’ll know exactly how it works and why it’s so powerful.

Key Takeaways:
* High-Level Concept: Self-attention uses sentence context to dynamically update word meanings, mimicking human understanding.
* The Process: Learn how attention scores, weights, and value matrices transform input data into context-enriched embeddings.
* Hands-On Code: See step-by-step how to implement self-attention in PyTorch, including creating embeddings and computing attention weights.

By understanding self-attention, you’ll unlock the key to understanding transformers and large language models.