Multi-Head Attention Dashboard

🎯 Multiple Perspectives on Language

Instead of using one attention mechanism, transformers use multiple "heads" that each specialize in different types of relationships. Select an example to see how different heads focus on different aspects:

👥 8 Different Attention Heads

Each head learns to focus on different patterns. Click on any head to see it enlarged:

🔍 Head Focus Detail

Head 1: Subject-Verb Relationships

This head specializes in connecting subjects with their verbs

Darker colors = stronger attention. Click on cells to see attention strength.

❌ Single Attention Head

One pattern recognition system
Limited perspective on relationships
Must handle all linguistic patterns
Jack-of-all-trades, master of none

Problem: Too many different types of relationships for one attention head to handle well.

✅ Multi-Head Attention

8 specialized pattern recognition systems
Each head focuses on specific relationships
Parallel processing of different aspects
Combined expertise from all heads

Advantage: Like having multiple experts each analyzing different aspects of language structure.

Key Insights

Specialization: Each head learns different linguistic patterns (syntax, semantics, etc.)
Parallel Processing: All 8 heads work simultaneously on the same input
Diverse Perspectives: Like having multiple critics analyze the same text
Combined Intelligence: Final output combines insights from all heads
Information Bottleneck: Each head operates in smaller dimension, forcing specialization