Part 15/20:
A recurring theme is the risk of overbuilding—if models do not improve sufficiently, the vast investments might lead to market saturation or downturns.
Risk of Overbuilding: Without continual model improvements, excess compute capacity could lead to a bubble burst, causing a recession, especially in the U.S. and Taiwan.
The Need for Model Improvement: To avoid waste, models must keep advancing—more sophisticated architectures, better training paradigms like reinforcement learning, environment interactions, and reasoning capabilities. These advances would justify massive investments and support the economic growth driven by AI.