China sweeping restrictions on rare earth exports threaten the U.S. defense industry, providing President Xi Jinping with a powerful leverage over President Donald Trump in upcoming trade talks.

Beijing will not allow the export of rare earth materials for use by foreign militaries, China’s Ministry of Commerce announced on Oct. 9. These are the first restrictions imposed by China that specifically target the defense sector, according to Gracelin Baskaran, a critical minerals expert at the Center for Strategic and International Studies.

“What this essentially means is that it will deny licenses to foreign militaries and companies that are producing military use end goods,” Baskaran told CNBC. “It undermines the development of the defense industrial base at a time when there is rising global tension. It is a very powerful negotiating tactic because it undermines national security.”

Rare earth magnets are crucial components in U.S. weapons systems such as the F-35 warplane, Virginia and Columbia class submarines, Predator drones, Tomahawk missiles, radars, and the joint direct attack munition series of smart bombs, according to the Department of Defense.

China dominates the global supply chain for rare earths. It controls 60% of mining and more than 90% of refining worldwide, according to the International Energy Agency. The U.S. is dependent on China for around 70% of its rare earth imports, according the U.S. Geological Survey.

“It’s scandalous that we don’t have a rare earths strategic reserve, that we let China monopolize 90% of the refining of rare earth materials,” Jeremy Siegel, University of Pennsylvania professor emeritus of finance, told CNBC on Monday. “Where were we?”

Beijing also imposed broad controls that require foreign companies to obtain an export license if rare earths processed in China make up as little as 0.1% of their products’ value. Firms also need licenses for products that rely Chinese rare earth technology for mining, smelting, separation, magnet manufacturing and recycling.

“If these rules were to be strictly and indefinitely enforced, they would be massively disruptive, not just to the US but globally,” Wolfe Research analyst Tobin Marcus told clients in an Oct. 10 note. Rare earths are also also crucial inputs for the semiconductor and automobile industries.

The restrictions would impact every sector of the U.S. economy but the defense, semiconductor and electric vehicle industry would face the brunt, according to Alicia Garcia Herrero, an economist at French investment bank Natixis. Defense contractors, Apple, Nvidia, Intel, Tesla, Ford and GM are all highly exposed, Hererro told clients in a Monday note.

The Trump administration is working to build out a domestic supply chain. The Defense Department struck an unprecedented deal with the largest U.S. rare earth miner MP Materials in July that included an equity stake, price floors and an offtake agreement.

“This will certainly also further accelerate US efforts to develop our own rare earth resources,” Marcus said. U.S. rare earth stocks have surged as investors speculate that the Trump administration will strike deals with other miners.

Trump and Xi are still expected to meet on the sidelines of the Asia-Pacific Economic Cooperation summit in Seoul, South Korea later this month, Treasury Secretary Scott Bessent told Fox Business on Monday.

The most likely scenario is “both sides pull back on the most aggressive policies and that talks lead to a further—and possibly indefinite—extension of the tariff escalation pause reached in May,” Goldman Sachs told clients Sunday.

But Beijing’s strategy is unclear and the tariff deadline is just weeks away, raising the risk that an agreement might not be struck in time, Marcus said.

“Without more conviction about Beijing’s strategy here, we’re concerned that they won’t be willing to back down fast enough to prevent these 100% tariffs from kicking in, at least temporarily,” the analyst said.

Sam Altman didn’t set out to compete with Nvidia.

OpenAI began with a simple bet that better ideas, not better infrastructure, would unlock artificial general intelligence. But that view shifted years ago, as Altman realized that more compute, or processing power, meant more capability — and ultimately, more dominance.

On Monday morning, he unveiled his latest blockbuster deal, one that moves OpenAI squarely into the chipmaking business and further into competition with the hyperscalers.

OpenAI is partnering with Broadcom to co-develop racks of custom AI accelerators, purpose-built for its own models. It’s a big shift for a company that once believed intelligence would come from smarter algorithms, not bigger machines.

“In 2017, the thing that we found was that we were getting the best results out of scale,” the OpenAI CEO said in a company podcast on Monday. “It wasn’t something we set out to prove. It was something we really discovered empirically because of everything else that didn’t work nearly as well.”

That insight — that the key was scale, not cleverness — fundamentally reshaped OpenAI.

Now, the company is expanding that logic even further, teaming up with Broadcom to design and deploy racks of custom silicon optimized for OpenAI’s workloads.

The deal gives OpenAI deeper control over its stack, from training frontier models to owning the infrastructure, distribution, and developer ecosystem that turns those models into lasting platforms.

Altman’s rapid series of deals and product launches is assembling a complete AI ecosystem, much like Apple did for smartphones and Microsoft did for PCs, with infrastructure, hardware, and developers at its core.

Unlike Nvidia and AMD chips, which are designed for broader commercial use, the new silicon is built for vertically integrated systems, tightly coupling compute, memory, and networking into full rack-level infrastructure. OpenAI plans to begin deploying them in late 2026.

The Broadcom deal is similar to what Apple did with its M-series chips: control the semiconductors, control the experience.

But OpenAI is going even further and engineering every layer of the hardware stack, not just the chip.

The Broadcom systems are built on its Ethernet stack and designed to accelerate OpenAI’s core workloads, giving the company a physical advantage that’s deeply entangled with its software edge.

At the same time, OpenAI is pushing into consumer hardware, a rare move for a model-first company.

Its $6.4 billion all-stock acquisition of Jony Ive‘s startup, io, brought the legendary Apple designer into its inner circle. It was a sign that OpenAI doesn’t just want to power AI experiences, it wants to own them.

Ive and his team are exploring a new class of AI-native devices designed to reshape how people interact with intelligence, moving beyond screens and keyboards toward more intuitive, engaging experiences.

Reports of early concepts include a screenless, wearable device that uses voice input and subtle haptics, envisioned more as an ambient companion than a traditional gadget.

OpenAI’s twin bet on custom silicon and emotionally resonant consumer hardware adds two more powerful branches over which it has direct control.

• OpenAI and Nvidia have agreed to a framework for deploying 10 gigawatts of Nvidia systems, backed by a proposed $100 billion investment.
• AMD will supply OpenAI with multiple generations of its Instinct GPUs under a 6-gigawatt deal. OpenAI can acquire up to 10% of AMD if certain deployment milestones are met.
• Broadcom’s custom inference chips and racks are slated to begin deployment in late 2026, as part of Stargate’s first 10‑gigawatt phase.

Taken together, it is OpenAI’s push to root the future of AI in infrastructure it can call its own.

“We are able to think from etching the transistors all the way up to the token that comes out when you ask ChatGPT a question, and design the whole system,” Altman said. “We can get huge efficiency gains, and that will lead to much better performance, faster models, cheaper models — all of that.”

Whether or not OpenAI can deliver on every promise, the scale and speed of Stargate is already reshaping the market, adding hundreds of billions in market cap for its partners, and establishing OpenAI as the de facto market leader in AI infrastructure.

None of its rivals appears able to match the pace or ambition. And that perception alone is proving a powerful advantage.

The company rolled out AgentKit for developers, new API bundles for enterprise, and a new App Store that offers direct distribution inside ChatGPT — which now reaches 800 million weekly active users, according to OpenAI.

“It’s the Apple playbook: own the ecosystem and become a platform,” said Menlo Ventures partner Deedy Das.

Until now, most companies treated OpenAI as a tool in their stack. But with new features for publishing, monetizing, and deploying apps directly inside ChatGPT, OpenAI is pushing for tighter integration — and making it harder for developers to walk away.

Microsoft CEO Satya Nadella pursued a similar strategy after taking over from Steve Ballmer.

To build trust with developers, Nadella leaned into open source and acquired GitHub for $7.5 billion, a move that signaled Microsoft’s return to the developer community.

GitHub later became the launchpad for tools like Copilot, anchoring Microsoft back at the center of the modern developer stack.

“OpenAI and all the big hyperscalers are going for vertical integration,” said Ben van Roo, CEO of Legion, a startup building secure agent frameworks for defense and intelligence use cases.

“Use our models and our compute, and build the next-gen agents and workflows with our tools. The market is massive. We’re talking about replaying SaaS, big systems of record, and literally part of the labor force,” said van Roo.

SaaS stands for software as a service, a group of companies specializing in enterprise software and services, of which Salesforce, Oracle and Adobe are part.

Legion’s strategy is to stay model-agnostic and focus on secure, interoperable agentic workflows that span multiple systems. The company is already deploying inside classified Department of Defense environments and embedding across platforms like NetSuite and Salesforce.

But that same shift also introduces risk for the model makers.

“Agents and workflows make some of the massive LLMs both powerful and maybe less necessary,” he noted. “You can build reasoning agents with smaller and specific workflows without GPT-5.”

The tools and agents built with leading LLMs have the potential to replace legacy software products from companies like Microsoft and Salesforce.

That’s why OpenAI is racing to build the infrastructure around its models. It’s not just to make them more powerful, but harder to replace.

The real bet isn’t that the best model will win, but that the company with the most complete developer loop will define the next platform era.

And that’s the vision for ChatGPT now: Not just a chatbot, but an operating system for AI.