So imagine you have a bunch of words in front of you and you want the computer to figure out which ones are most important or related to each other. Instead of just looking at one word at a time, self-attention lets it look at all the words together and see how they’re connected.

Here’s an example: let’s say we have the sentence “The quick brown fox jumps over the lazy dog.” If you want to find out which words are most important for understanding what happens next, self-attention can help. It looks at all the words and sees that “fox” is pretty important because it’s in the middle of an action (jumping) and there’s a clear subject (“the”) and object (“lazy dog”).

But how does this actually work? Well, let me break it down for you. First, we have to feed all our words into the computer as numbers using something called “embeddings.” These are just fancy math tricks that turn text into numbers so the computer can understand them better. Once we’ve got these embeddings, we pass them through a bunch of layers (called “transformers”) that help us figure out which words are most important for understanding what comes next.

The key part here is something called “self-attention.” This lets the computer look at all the words together and see how they’re connected. It does this by creating a bunch of little attention heads (like mini brains) that can focus on different parts of the text. Each head looks at a specific word and sees which other words are most important for understanding what comes next.

So let’s say we have three attention heads: one looking at “quick,” one looking at “brown,” and one looking at “fox.” The first head might see that “the” is pretty important because it helps us understand who or what the quick brown fox is (i.e., a subject). But then it looks at “jumps” and sees that “over” is also really important for understanding what happens next (i.e., an action). Finally, it looks at “lazy dog” and sees that this helps us understand who or what the quick brown fox jumps over (i.e., an object).

It does this by creating little attention heads that can focus on different parts of the text and see how they’re connected. And best of all, it works really well!