OpenAI to IPO? “For-Profit” Status Emerges

OpenAI is now officially a for-profit public profit corporation, with its nonprofit parent retaining a 26–27 percent stake to oversee research priorities. The restructure, approved by California and Delaware regulators, frees OpenAI to boost capital without limits and chase big, audacious AI projects, including the pursuit of artificial general intelligence (AGI).

Microsoft holds a 27 percent stake, keeps IP rights to OpenAI’s models through 2032, and may independently pursue AGI, but OpenAI can not simply declare AGI by itself anymore. Any claim have to be verified by an independent expert panel first. Each firms can still chase AGI independently, and Microsoft can team up with other partners, though compute thresholds are in place if it uses OpenAI’s IP.

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Infrastructure is at a staggering scale. OpenAI has already committed $1.4 trillion to roughly 30 gigawatts of information center capability and goals to scale as much as a gigawatt per week at $20 billion per gigawatt. This scale underpins OpenAI’s next big goal: a totally autonomous “legitimate AI researcher” by 2028, following an intern-level research assistant milestone in 2026. Jakub Pachocki, chief scientist, explains these systems will leverage expanded “test time compute,” letting models dedicate entire data centers’ price of processing power to unravel complex problems.

Meanwhile, OpenAI now flags that over 500,000 ChatGPT users weekly may show signs of mania or psychosis, with tens of millions more relying heavily on the chatbot for emotional support. To handle this, GPT-5 was retrained with guidance from 170 psychiatrists and clinicians. The most recent update, “gpt-5-oct-3,” adds clinical taxonomies, hotline redirects, and session-break nudges to detect distress without acting as a therapist.

Power is now a part of the equation. In a proper pitch to the White House, OpenAI warned that America’s AI ambitions hinge on energy, bluntly calling electricity “the brand new oil.” Its Stargate data centers alone will demand 10 GW, enough to power eight million homes, and the corporate is pushing for 100 GW per yr nationally to support next-gen AI workloads. Read more.

Nvidia just made its biggest pitch yet to own the long run of computing. At GTC DC 2025, Jensen Huang laid out an aggressive plan, all designed to cement Nvidia because the backbone of America’s tech infrastructure.

The centerpiece is the “AI factory,” massive data centers built with the Department of Energy and Oracle to simulate and train industrial-scale AI systems. The primary, Equinox, will pack 10,000 Blackwell GPUs; its follow-up, Solstice, targets 2,200 exaflops of compute – orders of magnitude beyond today’s AI clusters. These facilities run on Nvidia’s Omniverse DSX, which lets engineers model gigawatt-scale campuses as physics-accurate digital twins before they’re even built.

Nvidia can be bringing its fastest AI chips home. Blackwell GPU production is now underway in Arizona, a part of a broader reshoring push that Huang says strengthens national security and cuts reliance on Taiwan. The corporate’s recent BlueField-4 DPU, with 800 Gbps throughput and 6x the compute, will offload networking and security work, freeing GPUs for pure AI acceleration.

Quantum computing took center stage with NVQLink, a high-speed, low-latency interconnect bridging GPUs with quantum processors. Designed alongside 17 quantum hardware startups and nine U.S. national labs, NVQLink enables hybrid quantum-classical computation and real-time error correction. It’s the primary real try to make quantum practical, using the CUDA-Q stack because the bridge between QPUs and AI supercomputers. Jensen Huang described NVQLink because the “Rosetta Stone” connecting classical and quantum systems.

Nvidia can be moving into telecom, investing $1 billion in Nokia and rolling out its ARC platform to power 5G and 6G networks with AI-driven efficiency. Strategically, Nvidia emphasizes global adoption of U.S. technology, with $500 billion in advanced chip bookings and plans to re-enter the Chinese market. Read more.

Microsoft’s recent Microsoft 365 Copilot Frontier Program drops a full suite of self-building AI tools designed to make software creation as easy as typing a sentence. App Builder can spin up complete business apps on Azure while Workflows automates each day grind tasks like emails, approvals, and scheduling across Teams and Outlook.

A lighter Copilot Studio lets users prototype their very own AI assistants trained on company data before scaling them into multi-agent systems. All the things runs under Microsoft’s enterprise-grade security and a brand new “agent inventory” dashboard for control freaks and compliance teams alike. It’s a daring push to democratize app creation and automation for lots of of tens of millions of staff, essentially bringing no-code tools to the guts of Microsoft 365. Read more.

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