Introducing computer use in Gemini 3.5 Flash

The hardware wars just got more interesting. Eight months after OpenAI announced a partnership with Broadcom to design custom chips, they've unveiled Jalapeño—their first inference processor built specifically for running large language models. This matters more than it might seem on the surface.

For years, NVIDIA has owned the AI chip market almost completely. They've been the indispensable middleman between AI companies and the compute they need. OpenAI revealing Jalapeño signals something fundamental shifting: the most valuable AI companies now believe they need to own more of their stack rather than depend entirely on a single supplier. This isn't just about cost optimization—though that's part of it. It's about control, reliability, and the ability to shape your own infrastructure as your capabilities evolve. When you're spending billions on inference to power a product millions of people use daily, outsourcing that critical path to someone else becomes a strategic risk.

What's particularly telling is the framing. OpenAI explicitly describes this as the first chip in a multi-generation platform. They're not saying "we built one inference accelerator." They're saying "we're building a complete computing platform optimized for our vision of how AI should work." That's the ambition of a company that intends to stay independent and control its own destiny. By the way, this also puts real pressure on other labs. If you're Anthropic or Meta, you're now watching OpenAI integrate vertically into silicon. That's a moat that's much harder to replicate than just having better training algorithms.

Meanwhile, Google quietly shipped something almost as significant: computer use built directly into Gemini 3.5 Flash. This is agent territory—not just a language model that can reason about tasks, but one that can actually navigate interfaces, click buttons, fill forms, and take actions across platforms. The combination of these two moves tells you where the real competition is heading. It's not about who has the biggest model anymore. It's about who can build the most capable and cost-efficient integrated system: better inference hardware, agents that can act autonomously, and the infrastructure to run both at scale.

What strikes me is how this reshapes the entire market structure. Six months ago, NVIDIA was the critical infrastructure layer everyone depended on. Now you've got OpenAI building silicon, Google shipping agentic capabilities natively, and the gap between "AI company" and "AI infrastructure company" getting blurrier. The question isn't whether Jalapeño will immediately dethrone NVIDIA—it won't. The question is whether this signals the beginning of the end of any single company's dominance in this space.