Understanding Transformer Architecture from Scratch

The Transformer architecture powers virtually every major AI model today. Yet many developers use it without understanding how it works. Let us fix that.
Attention Is All You Need:
The key insight: instead of processing sequences step-by-step, Transformers process all tokens simultaneously. The attention mechanism lets each token look at all other tokens to determine relationships.
Key Components:
Positional Encoding: Adds order information since attention is order-invariant.
Multi-Head Attention: Multiple attention mechanisms running in parallel, each learning different aspects of relationships.
Feed-Forward Networks: Applied per-token to add non-linearity.