Why GPTs Don’t Use All Their Neurons

What if a language model didn’t need to use all of its parameters for every token? Early Transformers activate everything at once — every layer, every neuron, every parameter. It works… but it doesn’t scale forever. In this video, we break down Mixture of Experts (MoE), the architectural breakthrough that allows modern models to scale to massive parameter counts without increasing computation per token. You’ll learn how sparse activation works, how expert routing is trained, and why MoE models can reach trillion-parameter scale while remaining computationally efficient. We cover: - Why…