Deep Learning, Attention, Transformers, Optical Computing, AI.
as BERT. They also proposed a hybrid architecture that replaced all but the last two attention layers in BERT with FT layers, which reached 97% relative accuracy, with only a minor penalty in training time and stability. This is a highly encouraging result, seemingly the undesirable scaling