@Fenng: Is SpaceX the biggest bubble in history? From a revenue perspective, it cannot support such a high market cap.
Summary
Questions the mismatch between SpaceX's valuation and revenue, suggesting it might be the biggest bubble in history.
View Cached Full Text
Cached at: 06/13/26, 08:36 PM
Is SpaceX the biggest bubble in history?
From a revenue perspective, it cannot support such a high market cap.
Similar Articles
@FinanceYF5: 1/ The largest wave of infrastructure spending in human history may only just be beginning. Morgan Stanley estimates that, including operating leases, hyperscalers and neocloud providers will spend nearly $3.4 trillion in 2027 and 2028. Two years. $3.4 trillion.
Morgan Stanley estimates that hyperscale cloud providers and neoclouds will spend nearly $3.4 trillion on infrastructure across 2027 and 2028, including operating leases, potentially marking the largest wave of infrastructure spending in human history.
@elonmusk: Congrats SpaceX team!
SpaceX 于2026年Q3实现146亿美元收入，同比增长161%，并成功完成首次创收的星舰任务，向星链星座发射了26颗Starlink V3卫星。
@FinanceYF5: Why Is AI Proxy OpenRouter Worth $7.5B? Explained in 6 Minutes — In Short: Because Money Flows Through It. Every Dollar You Spend on Model Calls Passes Through OpenRouter First, and It Takes a 5.5% Cut. Its Peer Portkey Never Touches the Money — and Sold for Only $117M (Palo Alto 10-K)…
Analysis of why OpenRouter is valued at $7.5B: The core reason is that as an AI model proxy, all model-call spending passes through it with a 5.5% cut, while a comparable company that doesn't handle money, Portkey, was acquired for only $117M — a valuation gap of over 60x.
@BenjaminDEKR: I've been skeptical of SpaceX's AI / compute plans in the past. (Some of the timelines, especially orbital datacenters …
A commentator shares their shift from skepticism to buying $SPCX stock, citing growing evidence that SpaceX is serious about its AI and orbital datacenter plans despite exaggerated-seeming timelines.
RGH-GNN : Risk-Gated Heterogeneous Graph Neural Network for Financial Fraud Detection
RGH-GNN 提出一种风险门控的异构图神经网络，将 LightGBM 生成的交易级风险分数作为边权重引导消息传递，以提升金融欺诈检测性能，在 IEEE-CIS 数据集上取得 0.914 的 AUC-ROC 并超越所有基线。