AIはチップ代に見合う$3Tの収益問題に答えられるのか?
SequoiaのDavid Cahnは、2026年に予想されるインフラ支出を正当化するには、AI業界に$3Tの収益が必要だと見積もっています。トークン価格の下落とモデルの低価格化により、この投資回収はますます困難になっています。
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.