AI基建支出泡沫浮现：Big Tech陷债务与负现金流

AI infrastructure boom shows cracks: Big Tech faces debt, negative cash flow, investor skepticism

Reports confirm that leading tech firms are experiencing record capital expenditures on AI infrastructure while reporting declining operating cash flow and rising long-term debt—prompting intensified scrutiny from investors on unit economics and time-to-ROI. Internal project pauses (e.g., two AI cluster expansions halted over PUE and latency KPIs) reveal tightening operational discipline. For early AI application teams, this signals a decisive shift: infrastructure scalability is no longer the primary bottleneck—efficiency, cost-per-inference, and vertical-specific ROI are. Startups should prioritize lean deployment strategies (e.g., quantized models, hybrid edge-cloud routing) and rigorously validate unit economics before scaling. Raising capital solely on infrastructure ambition is increasingly insufficient; investors now demand clear paths from model output to measurable customer value and margin.