The claim that 96% of Claude and GPT-5's weights are “literally useless”

A user sharing a video they describe as an 18-minute scaling explainer argues that most of Claude and GPT-5's weights—the numerical parameters inside a neural network—are unnecessary. Citing what they describe as 2019 MIT research, they claim a much smaller “winning lottery ticket” network does the real work. The post uses that argument to claim AI labs waste 90%-plus of their Nvidia budgets.