Here’s what’s worth your time today.
SpaceX is reportedly preparing a record-breaking IPO that could value the company at up to $1.75 trillion, bundling together rockets, satellites, and AI after folding in xAI. The scale alone would make it the largest IPO ever, but the real twist is what investors are being asked to buy: a fast-changing conglomerate with massive AI ambitions and unclear financials. With losses piling up across AI infrastructure, this could become the first real test of whether public markets will back the “spend now, figure it out later” model — and set the tone for how companies like OpenAI and Anthropicapproach going public next.
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A growing split is emerging between Elon Musk and leaders at companies like OpenAI and Anthropic. Musk is pushing a faster, less constrained approach to AI, while others are leaning into guardrails and safety. Insiders say the tension runs deep, with rivals actively positioning themselves in opposition to his style. The result is a new kind of competition: not just over models and capabilities, but over how far AI should go, and how quickly.
SoftBank taking on a $40 billion short-term loan to fund its massive investment into OpenAI is a strong signal the market expects an IPO sooner rather than later. The loan is unsecured and due within 12 months, suggesting lenders are betting on OpenAI going public in time to provide liquidity. If that plays out, it wouldn’t just be one of the biggest IPOs ever, it would also validate the huge capital flowing into AI — and test whether public markets are ready to back it.
DeepSeek suffered a rare outage lasting more than seven hours, disrupting access for users across China and forcing multiple fixes before services began stabilising. The company has typically maintained near-perfect uptime, which makes the incident stand out. The bigger takeaway is simple: as AI becomes core infrastructure, reliability matters as much as capability. Even leading models aren’t immune to failure, and as usage scales, downtime becomes a real business risk.
Oracle says it won’t charge extra for AI, but the real shift is happening under the surface. As AI agents increase usage dramatically, traditional seat-based pricing starts to break, pushing SaaS toward consumption or outcome-based models. One user could soon trigger thousands of automated actions, making “per seat” irrelevant. The signal is clear: AI isn’t just changing products, it’s forcing a full rethink of how software gets priced — and who ends up paying more.