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hello there today were looking at fnet mixing tokens with fourier transforms by james lee thorpe joshua ainsley ilya eckstein and santiago antonion of google research i know im a bit late with this one but its sort of a not only this paper but its a really interesting direction thats happening right now in machine learning in general in deep learning in sequence models in image models and so on and that is the sort of giving up of attention mechanisms so for the longest time weve been focusing on transformers and in a transformer you technically you have some sort of a sequence as an input and then you push that through these attention layers the layers are actually always made up of attention sub layers and then feed forward layers so every layer would have an attention sub layer and a feed forward sub layer or multiple ones of them now the feed forward sub layers they would be sort of acting individually on the elements so the weights are shared there is one feet forward layer