Scaling LLMs won't get us to AGI. Here's why.

A viral Reddit post argues that scaling current transformer-based LLMs will never achieve Artificial General Intelligence (AGI). The author contends transformers are fundamentally pattern matchers, brilliant at interpolation but incapable of the novel extrapolation and causal reasoning required for true understanding. They claim AGI needs a new architecture that builds causal world models and learns from minimal data, not just more compute. This challenges the core 'scaling hypothesis' driving industry investment.