A prominent AI research lab argues that achieving Artificial General Intelligence (AGI) is primarily a matter of engineering and resources, suggesting that if they could build a model with a trillion parameters and train it on the entire internet, AGI would be the inevitable result. Based on the understanding that simply increasing model size may not be sufficient, identify and explain one fundamental limitation or missing capability in current model architectures that this 'scaling-only' approach fails to address.