My understanding is that transformers are now favored over RNNs because they parallelize better. It's hard to imagine, but I wonder if there's some non-paralle

My understanding is that transformers are now favored over RNNs because they parallelize better. It's hard to imagine, but I wonder if there's some non-parallelizable machine learning algorithms which might outperform these massive models? It seems improbable, but it's a small hope I've had. The greatest intellects were aware of (ourselves) do not scale very well, and maybe the same will ultimately apply to AI?