Chinese electric vehicles face 125% cumulative tariffs, a proposed Senate ban, and fierce opposition from lawmakers and the US auto industry. But there is a growing possibility that Chinese EVs will be sold in the US within the next few years. The routes in are multiplying: through Canada, Mexico, and partnerships with the very automakers that publicly oppose them.

China captured nearly 75% of global EV manufacturing and 40% of global EV trade in 2025, according to the International Energy Agency. Production of 16 million electric cars outstripped domestic demand by 20%, pushing exports to a record 2.5 million. “The only market in the world they have not yet penetrated is the United States,” said Michael Dunne, CEO of Dunne Insights.

The Big Three are in an awkward position. Ford, GM, and Stellantis have retreated from aggressive EV plans while most experts agree electrification is the future. “U.S. companies have stepped back from a lot of their electric vehicle campaigns, because they haven’t been able to develop, in an inexpensive way, a compelling value proposition,” said Stephen Dyer of AlixPartners. “You can’t be competitive if you’re not in the game.”

Yet all three are quietly deepening ties with Chinese automakers. Ford is in talks with Geely to create a European partnership and, according to The Wall Street Journal, “appears to be opening the door to allowing Chinese cars in the U.S. at some point.” GM imports CATL battery cells for its Chevy Bolt. Stellantis owns 21% of Leapmotor and a 51% majority of a joint venture that its CEO said could expand into Mexico and Canada.

Geely is already using Volvo’s plants rather than building new factories, giving it manufacturing bases in both Europe and the US without greenfield investment. The Volvo factory near Charleston, South Carolina, could be adapted for other Geely platforms, including Zeekr, the brand Waymo uses for its robotaxi fleet.

Chinese EVs are already arriving in Canada, where Prime Minister Mark Carney signed a deal in January permitting up to 49,000 Chinese-built EVs annually at a 6.1% tariff rate. In Mexico, Chinese vehicles account for a quarter of total sales. BYD and Geely are among finalists vying to purchase a Nissan-Mercedes plant there. GAC announced plans to begin assembly in Mexico this year.

Trump expressed support in January for letting Chinese companies manufacture in the US, provided they employ American workers. But hurdles remain. A Senate bill to permanently ban Chinese automakers has bipartisan backing. Regulations restrict Chinese-developed software in connected vehicles. And the USMCA trade deal is up for renewal, with the Trump administration pushing for a new US-content requirement in vehicles.

Even the border is becoming porous. Chinese EVs from BYD, Geely, and Xpeng are showing up along the US-Mexico border, purchased at Mexican dealerships for under $20,000 by citizens who commute to US border cities. Registration in the US is nearly impossible, but the demand signal is clear. According to Kelley Blue Book, 38% of Americans would consider buying a Chinese vehicle.

China’s domestic market is also pushing companies outward. EV and hybrid sales in China fell 6.8% year-over-year in April. Overall vehicle sales dropped 21.5%. Overcapacity and intensifying competition mean Chinese automakers must export to survive.

“By 2030, we will see some form of Chinese cars on American roads,” Dunne said. “One way or another, they’ll find their way in.” The question is whether Detroit will be a partner or a bystander when they do.

Megaport spent a decade as a company you used to connect to other people’s clouds. On Wednesday it announced a plan to become one. The Australian networking firm secured four new AI infrastructure contracts worth a combined A$458.9M (about $329M) and launched a fully underwritten entitlement offer to raise A$827.3M (about $594M), according to its filing. The money funds a pivot from plumbing to compute.

The contracts come first. All four are with US-based technology providers running AI applications, are expected to start in the first half of 2027, and require nearly A$369.5M in capital expenditure, mostly for high-performance Nvidia GPUs alongside network and storage. That is a meaningful commitment for a company of Megaport’s size, and it explains why the raise is so large relative to the business.

What the capital is really buying is the strategy behind the contracts. Megaport says it will build a globally distributed AI inference cloud, anchored by an on-demand GPU pool backed by about A$350M in investment and offered to enterprise customers on both contracted and consumption-based pricing.

The pool is to be deployed across the company’s existing footprint of more than 1,100 connected data centres in 31 countries, with rollout over the next six to nine months.

The bet is geographic. Most GPU capacity today sits in a handful of enormous data centres optimised for training the largest models. Megaport is targeting the other half of the AI workload: inference, the act of running a trained model to answer a query, which benefits from being close to the user.

Its pitch is that a distributed network of smaller GPU pools, spread across the data centres it already connects, fits inference better than centralised mega-campuses, and slots into the gap between hyperscaler clouds and single-location GPU specialists.

It is a credible reading of where AI infrastructure is heading. As models move from research demos into products embedded in real applications, the economics shift from training to serving, and serving rewards proximity and distribution.

Megaport already owns the network that links the locations where that compute would live, which is a genuine structural advantage if the thesis holds.

The numbers around the raise were briefly muddled across early coverage, which is worth untangling. The four contracts are worth A$458.9M in total contract value; the capital raise is A$827.3M; the GPU pool commitment is about A$350M.

Several headlines collapsed these into a single figure. They are distinct: contract wins, the money to fund them, and the specific compute investment inside that money.

Megaport also tightened its 2026 revenue guidance to A$307M–A$315M and projected combined group pro forma annual recurring revenue of A$662.9M once the compute division is folded in. The shares were halted while the raise was arranged, a standard mechanism for a deal of this scale on the ASX.

The risk is the obvious one for any company spending heavily on Nvidia GPUs on the strength of contracts that begin in 2027: that AI infrastructure demand, and pricing, may look different by the time the hardware is installed and earning.

Megaport is committing capital now against revenue that lands later, in a market moving fast enough that 18 months is a long time. The contracts give it a floor. The inference-cloud ambition is the part that has to compound, and that is the part the A$827M is really betting on.

Nvidia opened Taipei’s enormous Computex trade show on Sunday with a spark, literally. The chipmaker unveiled a new PC CPU called the RTX Spark, which it dubbed a “superchip,” and named a who’s who list of PC makers that will soon deliver AI PCs powered by it.

The super-fast, 1-petaflop chip is designed to run AI agents like OpenClaw or Hermes Agent securely, according to Nvidia. Such RTX Spark Windows PCs will be available this fall from ASUS, Dell, HP, Lenovo, Microsoft Surface, and MSI, with models from Acer and Gigabyte to follow.

In addition to being equipped with secure sandboxes (jointly developed with Microsoft) to run agents securely, the PCs will also have enough CPU, GPU, RAM, and underlying Nvidia CUDA software to run local versions of large language models.

Nvidia said that its RTX technology will deliver faster performance for AI, better image quality, and support for AI features in more than 1,000 games and applications.

The chipmaker is marketing this as an alternative for creators making AI content, as well as providing a significant upgrade to its traditional market of gamers. Nvidia said more than 100 Windows software makers have signed on to support the new chip, including Adobe, Blender, ComfyUI, Riot Games, and Xbox.

But Nvidia founder and CEO Jensen Huang’s vision for these new PCs is far larger. He wants to end the days of launching apps, pointing, clicking, and typing.

“With RTX Spark and Microsoft Windows, you ask — and the PC does the work,” he said in the press release. “Frontier models. Creative workflows. RTX games. All on a laptop.”

Last month, after delivering another record quarter, Huang promised investors he had found a new $200 billion market for Nvidia in selling CPUs for AI, not just GPUs. He made specific mention of the high-end server CPU released earlier this year called Vera — of which Nvidia says it has already sold $20 billion worth.

He also hinted at his bigger ambitions. “We’ll have billions of agents, and those billions of agents will all use tools. And those tools are going to be like PCs, just like us humans using PCs today,” he said on the earnings call in May. “We’re going to need a lot more CPUs.”

Nvidia ARM-based Windows devices have been tried before — and failed. Back in 2013, Microsoft famously had to write off $900 million on its Nvidia ARM-based Surface RT, with partners like Dell also bailing on the product.

But at this point, after delivering record after record of quarterly revenue, it’s hard to bet against Huang as he pursues his PC dreams once again.

And this chip is an entirely different beast. It’s more powerful, not less. Microsoft is positioning its own RTX Spark PC as so mighty that it named it the Surface Laptop Ultra, and is calling it “the most powerful Surface Laptop ever built.”

Still, PC manufacturers have not released a lot of specifics about each of their offerings, including pricing. These systems appear to be full-fledged Windows versions of the DGX Spark mini-computer that Nvidia already sells to developers for about $4,800.

We’ll have to wait and see if these PCs will compete on price with the affordable Mac Mini that has become a popular choice for running OpenClaw. Or perhaps they will sit at the high end of the PC market, like Nvidia’s own agent-running mini computer.

Either way, if Nvidia has cracked the code on bringing AI agents easily, safely, and usefully to the masses, it could — and should — be big.