Andrew Ross Sorkin
Sam Altman never intended to turn OpenAI into a hardware powerhouse. When the company was founded, its philosophy was simple: the key to unlocking artificial general intelligence lay in superior ideas, not massive infrastructure. Yet over time, that belief evolved. Altman and his team discovered through experience that scale — the sheer volume of computing power — was not just helpful but essential. More compute meant smarter models, faster progress, and ultimately, industry dominance.
That realization has now taken shape in one of OpenAI’s most ambitious moves yet. On Monday, Altman revealed a sweeping new partnership that pulls OpenAI directly into the semiconductor business, positioning it in closer competition with tech giants like Nvidia and Amazon. The company announced it will work with Broadcom to co-develop racks of specialized AI accelerators designed exclusively for OpenAI’s own workloads. For a company once convinced that intelligence would emerge from clever algorithms alone, this marks a decisive shift toward the physical foundations of AI.
Speaking on OpenAI’s company podcast, Altman reflected on the turning point: “In 2017, we discovered that scaling up gave us the best results. It wasn’t a theory we set out to prove — it was something we found empirically after seeing everything else perform worse.” That single insight, that size and speed could outpace ingenuity, transformed OpenAI’s direction forever.
The Broadcom collaboration extends that philosophy. Together, the two companies will design and deploy fully integrated racks of custom silicon, optimized specifically for OpenAI’s model training and inference workloads. The goal is deeper vertical control — from chips and data centers to APIs and developer tools — creating a seamless ecosystem that connects every layer of AI production. It’s a strategy that mirrors the playbooks of Apple and Microsoft, both of which built entire product empires around owning the stack: hardware, software, and developers.
Through Broadcom, OpenAI is now co-creating chips purpose-built for inference — highly tuned to its internal models rather than general commercial use. Unlike Nvidia or AMD chips, which must serve a wide range of industries, OpenAI’s silicon is tightly integrated with memory, networking, and compute into full rack-level systems. The first deployments are expected in late 2026, giving OpenAI hardware built specifically for its models and workloads. The comparison to Apple’s M-series chips is unavoidable: by controlling the semiconductors, a company can control the user experience. But OpenAI is going even further, taking responsibility for every layer of its physical architecture, not just the chips themselves.
Broadcom’s systems, based on Ethernet technology, are tuned to accelerate OpenAI’s heaviest workloads, offering a hardware advantage that merges directly with its software capabilities. This tight coupling could help the company deliver faster, cheaper, and more efficient AI models while maintaining proprietary control over the infrastructure that powers them.
In parallel, OpenAI has been moving into consumer hardware — a surprising direction for a company long known for its software-first identity. Its $6.4 billion acquisition of Jony Ive’s design startup, io, signaled a new era for OpenAI. Ive, the former chief designer at Apple, brings a design philosophy centered on simplicity and human connection. With him, OpenAI isn’t just building tools for AI; it’s designing experiences for living with it. Early reports suggest prototypes include wearable, screenless devices that use voice and touch rather than traditional displays — envisioned less as gadgets and more as intelligent companions.
This dual focus — developing its own silicon and creating emotionally resonant AI devices — represents two powerful new fronts under Altman’s control. Both serve the same ambition: to make OpenAI the center of a self-sustaining AI ecosystem where everything, from raw compute to user experience, flows through its own hands.
These efforts converge under a larger campaign internally referred to as “Stargate,” OpenAI’s coordinated plan to build the physical and digital backbone of next-generation AI. The scope of Stargate is staggering. Over the past month, OpenAI has finalized several major partnerships totaling hundreds of billions of dollars in potential value. One deal outlines a framework with Nvidia to deploy 10 gigawatts of GPU infrastructure, backed by as much as $100 billion in proposed investment. Another agreement secures multiple generations of AMD’s Instinct GPUs, ensuring long-term supply and offering OpenAI an option to purchase up to 10 percent of AMD if certain deployment goals are met. Broadcom’s custom accelerators, meanwhile, will begin rolling out as part of Stargate’s first 10-gigawatt phase in 2026.
Taken together, these moves give OpenAI unprecedented end-to-end control over its technological stack. “We can think about everything from the transistor level up to the token you see when you ask ChatGPT a question,” Altman said recently. “Designing the whole system ourselves gives us massive efficiency gains — faster models, cheaper models, better performance across the board.”
Even if every promise doesn’t materialize immediately, the scale and velocity of Stargate have already reshaped the market. OpenAI’s partners — Nvidia, AMD, and Broadcom — have seen their valuations soar, while competitors scramble to keep up. None seem capable of matching the company’s tempo or integration. In an industry driven by perception and momentum, that may be enough to secure OpenAI’s lead.
Yet Altman’s strategy doesn’t stop at infrastructure. OpenAI is also staking its future on developers — the community that transforms raw AI power into real-world products. At its recent DevDay, the company showcased how it’s building not just models but a full platform for creators. Gil Luria, head of technology research at D.A. Davidson, noted that OpenAI now competes simultaneously in three arenas: frontier models, consumer applications, and enterprise APIs. “They’re competing with every major tech company in at least one of these markets,” he said. “Developer Day showed how OpenAI is helping others integrate its models directly into their own systems. The tools were impressive and remarkably user-friendly.”
Still, Luria added, OpenAI faces stiff competition from giants like Microsoft Azure, Amazon Web Services, and Google Cloud — all with deeper financial reserves. But OpenAI’s aggressive push to unify developers under its banner may offset that imbalance. The company introduced AgentKit, a toolkit for building AI agents, alongside new enterprise API bundles and an in-ChatGPT App Store that lets developers distribute and monetize their creations directly within the platform. With ChatGPT reportedly reaching 800 million weekly active users, the App Store represents a massive built-in audience.
As Menlo Ventures partner Deedy Das observed, “It’s the Apple strategy all over again — own the ecosystem and become the platform.” Many developers once treated OpenAI as just another API provider. Now, by offering integrated tools for publication, monetization, and deployment, OpenAI is making it harder to leave. It’s no longer a component — it’s becoming the core.
Microsoft used a similar playbook when Satya Nadella took over the company, rebuilding developer trust by embracing open source and acquiring GitHub. That acquisition later produced Copilot, which re-anchored Microsoft’s relevance in the developer world. OpenAI appears to be following a parallel trajectory, but with AI as its foundation instead of software.
Ben Van Roo, CEO of Legion Intelligence, a startup developing agent frameworks for defense and intelligence, described it succinctly: “All the big AI companies are going for vertical integration. They want you to use their models, their compute, and their tools to build next-gen agents. The potential is enormous — we’re talking about replacing major SaaS systems and parts of the labor force itself.”
Van Roo’s own firm is taking the opposite route, remaining model-agnostic and focusing on secure, interoperable workflows that connect across multiple platforms like Salesforce and NetSuite. But he acknowledges the trade-offs: “The rise of agents and specialized workflows could make some of these massive language models both more powerful and, paradoxically, less essential. You can create reasoning agents without needing something as large as GPT-5.”
That paradox underscores why OpenAI is racing to lock down every element of its ecosystem. The company understands that the future of AI may depend less on having the most advanced model and more on controlling the surrounding network of tools, infrastructure, and developers. By building a closed loop — from silicon to software to end-user experience — OpenAI aims to define the next era of computing itself.
In that vision, ChatGPT is no longer just a chatbot. It’s the foundation of a new operating system for artificial intelligence — one that could reshape not just how machines think, but how humans build, communicate, and interact with them.
