The article discusses the slowing pace of innovation in artificial intelligence (AI) and the growing challenges associated with its implementation and profitability. Despite significant investments and high expectations, AI's improvement rate is decelerating, and it is becoming less efficient due to the saturation of available training data. Large-scale companies may sustain their AI ventures with vast resources, but AI startups face difficulties competing and surviving. Additionally, high operational costs and limited practical applications put into question AI's potential to generate significant returns, much like the fiber-optic boom of the late 1990s that led to a market crash. Evidence also suggests that AI is not the productivity booster it was projected to be, creating skepticism about its transformative impact on industries and jobs.
