AI 能否回答 3 万亿美元营收问题以支付芯片费用？
红杉的 david cahn 估计，ai 行业需要 3 万亿美元的营收来证明 2026 年预计的基础设施支出是合理的。不断下跌的代币价格和更便宜的模型使得这一回报变得越来越困难。
sequoia's david cahn updated his analysis on ai infrastructure spend, projecting that the industry must earn $3 trillion to cover the $1.5 trillion capex for chips and data centers expected by 2026. this required revenue per gigawatt has risen due to memory costs and bottlenecks, with current leaders like openai and anthropic falling short of the necessary volume. apollo chief economist torsten slok highlighted risks to this payback, noting that hyperscalers predict cash flow accelerations by 2028 but face headwinds from cheaper open-weight models and rapidly declining token prices. slok warns that failure to meet these revenue targets could tip the economy into recession and force an s&p 500 correction, as the entire market rally currently depends on these few companies.