然而，這種補貼模式正走向終結，許多人工智慧服務開始轉向基於使用量的定價。這導致用戶開始限制使用量，並轉向成本更低且多為開源的中國人工智慧模型。這引發了人們對巨額人工智慧投資能否轉化為實際利潤的質疑，甚至擔憂人工智慧技術會像電力一樣商品化，使得基礎設施投資面臨巨大風險。
總結來說，目前的人工智慧熱潮建立在該技術將實現盈利且需求將迅速普及的兩大假設之上。然而，普及速度可能需要長達十五年的時間，且主要科技公司資本支出的激增與其股價停滯不前形成了強烈對比。這表明，儘管人工智慧技術本身令人興奮，但作為一項投資交易，市場的過度熱情可能隱藏著資本錯配的危機。
Despite a significant increase in second-quarter earnings for TSMC, its shares and the broader tech market fell due to soaring expectations for the chip and AI industries. For a long time, AI model makers offered services below cost to attract users and fuel the chip boom, while investors willingly covered these losses in anticipation of massive future returns.
However, this subsidy model is coming to an end as many AI services transition to usage-based pricing. This shift has led users to ration their consumption and pivot towards lower-cost, predominantly open-source Chinese AI models. It raises serious doubts about whether immense AI investments can translate into actual profits, sparking fears that AI might become commoditized like electricity, thereby jeopardizing infrastructure investments.
In conclusion, the current AI trade relies on the two major assumptions that the technology will be profitable and that widespread demand is imminent. Yet, mass adoption could take up to fifteen years, and the surge in capital expenditures by major tech companies contrasts sharply with their stagnant stock prices. This suggests that while AI technology itself is exciting, the market's exuberance as an investment trade may conceal a crisis of capital misallocation.