LLMs Without Deep Neural Networks: New Architecture, Benefits and Case Study

This article presents a novel architecture for LLMs that eliminates the need for deep neural networks. The proposed model, building on RBF networks, finds the global optimum of the loss function in a single iteration, thereby removing the tedious training step.