to be um to be kind of like what you learn in a convolution not exactly so um no i i think i made a mistake and we'll see it in the formula we'll see it in the formula yeah okay so here they introduce these positional embeddings okay so you see that we previously we had the soft max previously we had this and this okay so this is the lower layer this is the information that comes into the layer and now it's it's transformed into values by a linear matrix but essentially this is the lower layer and for each of