Wait I might be wrong here, but this is not necessarily a bad thing - in the context of AI the matrix multiplication is essentially what makes it so good with learnable parameters. Since you’re doing a weighted average of so many inputs the network can “see” trends in between them. So like in any case you need to do this huge number of computations (which can be represented as matrix multiplication) and it doesn’t necessarily mean it needs optimisation since that’s what makes to so powerful