OpenAI needs to raise at least $207B by 2030 so it can continue to lose money (ft.com)

A new analysis says OpenAI will need to raise at least $207 billion by 2030 just to sustain its current business model of heavy investment and ongoing operating losses. That headline number captures projected cash burn across compute, data-center buildout, staff, and R&D for larger models, safety work, and product scaling — essentially the capital required if OpenAI doesn’t quickly turn deep losses into sustained profits. The sum highlights how the economics of cutting‑edge LLM development remain dominated by massive upfront and recurring hardware and energy costs, plus continued spending on fine-tuning, safety alignment, and latency‑reduction for real‑time services. For the AI/ML community, the implication is twofold: technical progress is capital‑intensive and vulnerable to funding cycles, and business-model outcomes will shape what research gets prioritized. Large capex needs can push companies toward revenue-driven decisions (pricing, gated features, enterprise focus) and deeper partnerships or dependencies on cloud and chip providers. It also raises competition and policy questions — who funds foundational models, how open-source alternatives fare, and how investor risk appetite will influence product roadmaps and safety investments. In short, the $207B figure is a reminder that sustaining frontier AI is as much a finance and infrastructure challenge as it is a research one.