Understanding Multi-Head Attention in Simple Terms

Imagine you’re reading a sentence, and you want to understand the meaning of each word in the context of the entire sentence. When you focus on one word, you might think about different aspects of that word: its role in the sentence, its relationship to other words, or even the tone or emotion it conveys.

Multi-head attention is like having multiple people (or “heads”) reading the same sentence, each focusing on different aspects of the words at the same time. Here’s how it works step by step:

1. Breaking Down the Attention

• Single Head: If you only had one person (one “head”), they’d look at a word and think about how it relates to every other word in the sentence. This is what we call self-attention. The person might decide that certain words are very important to understand the current word, while others are less important.
• For example, in the sentence “The cat sat on the mat,” if you’re focusing on the word “sat,” you might consider “cat” as important because it tells you who is sitting. But “on” might be less important in this context.

2. Why Multiple Heads?

• Different Perspectives: Now, imagine that instead of just one person (one head) doing this, you have several people (multiple heads). Each person can focus on different aspects of the sentence:
• One might focus on grammatical relationships (like subject and verb).
• Another might focus on the meaning of the words.
• A third might focus on the position of the words in the sentence.
• By having multiple heads, the model can understand the word from several angles at once, getting a richer and more detailed understanding.

3. How It Works

• Parallel Processing: Each “head” works independently, performing self-attention on the same sentence but with a different focus. They all look at the sentence, decide which words are important for the word they’re focusing on, and then produce their own understanding or “attention scores.”
• Combining Results: After each head has done its job, their results are combined. Think of it like having a group discussion where everyone shares their insights. You then take the best parts of each person’s perspective and combine them into a final, well-rounded understanding.

4. Example in Action

Let’s go back to the sentence “The cat sat on the mat.”

• Head 1: Focuses on the subject-verb relationship and figures out that “cat” and “sat” are closely related.
• Head 2: Focuses on spatial relationships and notices that “sat” and “on” are related because the cat is sitting on something.
• Head 3: Focuses on objects and realizes that “mat” is important because it’s the thing the cat is sitting on.

Each of these heads gives its own set of insights, which are then combined to form a more comprehensive understanding of the sentence.

5. Why Is This Useful?

In language, meaning is often subtle and layered. By using multi-head attention, the Transformer model can capture these subtleties more effectively. It’s like having multiple pairs of eyes on the same problem, each seeing something slightly different, which leads to a much richer interpretation.

Summary

• Multi-head attention is like having multiple people (heads) analyzing the same sentence from different perspectives.
• Each head performs self-attention independently, focusing on different aspects of the words.
• The insights from all the heads are combined to form a deeper and more nuanced understanding.

This method makes the Transformer model powerful and capable of handling the complexities of natural language, helping it excel in tasks like translation, text generation, and more.