Why is simple matmul of embedding vectors describes theirs similarity?

[gent.spah]

The principle is what I wrote above, its like cosine similarity and measuring distance between representations of words in embeddings, as well as finding where the attentions is placed on the sentence.

Have a look on this post here in the forum:

Confusion about Q, K, and V matrices

Can someone explain clearly on what exactly are the Q, K, and V matrices? How exactly do we get the value vector? I know that Q contains the embeddings for the words that we want to be translated and K contains the embeddings for the words that are the translated ones. So what exactly is V and how do we obtain it? Another question is that in multi-headed attention, we multiply the words (embeddings) that we want to be translated with Q, K, and V matrices, but doesn’t Q itself contains the embe…