China plans to block US investment in its top AI firms without government approval


Two parallel moves in 24 hours mark a significant escalation of the US-China AI war from chips and exports into capital and models. 

China plans to restrict its leading technology companies, including top AI startups, from accepting US capital without first obtaining government approval, Bloomberg News reported on Friday, citing people familiar with the matter.

No Chinese government official confirmed the report. The move, if implemented, would represent a significant structural shift in how Chinese AI companies access foreign capital, effectively placing US venture capital into the same approval framework that already governs certain technology exports, data flows, and foreign acquisitions of Chinese assets.
The timing is not accidental.

On Wednesday, the Trump administration announced it would crack down on foreign technology companies, singling out China, that are “exploiting” US artificial intelligence models, a practice known as model distillation.

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White House Director of Science and Technology Policy Michael Kratsios framed the move as the first major US government response to complaints from Silicon Valley AI companies that Chinese developers have been using open-source or commercially accessible US AI models as training data to build rival-generation systems, thereby closing the capability gap without having to develop from scratch.

Bloomberg characterised the US move as targeting Chinese firms “improperly” using American AI models.

Together, the two announcements describe a 24-hour escalation in which both governments moved simultaneously to sever the remaining channels of AI technology and capital transfer.

The US is trying to prevent its models from being used to train Chinese competitors; China is trying to prevent American money, which carries intangible benefits including managerial expertise, talent networks, and strategic access, from flowing into its AI national champions without state oversight.

Each move is a response to the other’s prior actions, and each creates the conditions for the next retaliation.

The backdrop to China’s reported capital controls is the existing US outbound investment rule that came into effect on 2 January 2025, which prohibits US persons from making equity investments in Chinese companies engaged in advanced semiconductors, quantum computing, or certain AI systems without Treasury Department approval or notification.

China’s reported plan is, in structural terms, the inbound mirror of that US rule: requiring government approval before Chinese AI companies accept capital from the country that has also been restricting chip exports to China since 2022.

The model distillation question is the more technically novel of the two moves. Chinese developers have used DeepSeek-R1, Meta’s open-source Llama models, and other accessible US models as training signal for their own systems, a practice that is currently legal under open-source licences but which US AI companies argue gives Chinese labs an unfair structural advantage.

DeepSeek V4-Pro, released earlier today and covered separately by TNW, was trained with Huawei chips and claimed near-frontier performance; whether it also incorporated distillation from US models is a question the administration’s new framework would directly address.

The enforcement mechanism for the distillation crackdown has not been specified publicly; the question of how a government would prevent training data from crossing borders is technically and legally unsettled.

The commercial implications for Chinese AI startups are significant but uncertain. Companies like Moonshot AI, Zhipu AI, MiniMax, and the entity formerly known as Manus AI have been navigating a capital environment that was already constrained by US regulatory signals.

If the approval requirement is implemented, it would add a formal layer of Chinese government oversight to any US VC investment in those companies, potentially chilling investment further or driving more of China’s AI capital formation through domestic channels.

The Chinese government has been increasing state investment in AI infrastructure and has made no secret of its preference for domestic AI champions over internationally capitalised ones. A formal approval regime for US investment would be consistent with that preference.

What neither measure resolves is the underlying dynamic driving it: China’s AI capabilities are improving faster than the export controls are degrading them. DeepSeek V4, released today, claims near-frontier performance on coding and mathematics using Huawei chips, not Nvidia ones.

The US controls on chip exports and investment were premised on a widening capability gap; that gap is narrowing. The question both governments are now answering is not “how do we maintain the current technological order” but “how do we shape the terms of a competition that is already fully joined.”



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Recent Reviews


As I’m writing this, NVIDIA is the largest company in the world, with a market cap exceeding $4 trillion. Team Green is now the leader among the Magnificent Seven of the tech world, having surpassed them all in just a few short years.

The company has managed to reach these incredible heights with smart planning and by making the right moves for decades, the latest being the decision to sell shovels during the AI gold rush. Considering the current hardware landscape, there’s simply no reason for NVIDIA to rush a new gaming GPU generation for at least a few years. Here’s why.

Scarcity has become the new normal

Not even Nvidia is powerful enough to overcome market constraints

Global memory shortages have been a reality since late 2025, and they aren’t just affecting RAM and storage manufacturers. Rather, this impacts every company making any product that contains memory or storage—including graphics cards.

Since NVIDIA sells GPU and memory bundles to its partners, which they then solder onto PCBs and add cooling to create full-blown graphics cards, this means that NVIDIA doesn’t just have to battle other tech giants to secure a chunk of TSMC’s limited production capacity to produce its GPU chips. It also has to procure massive amounts of GPU memory, which has never been harder or more expensive to obtain.

While a company as large as NVIDIA certainly has long-term contracts that guarantee stable memory prices, those contracts aren’t going to last forever. The company has likely had to sign new ones, considering the GPU price surge that began at the beginning of 2026, with gaming graphics cards still being overpriced.

With GPU memory costing more than ever, NVIDIA has little reason to rush a new gaming GPU generation, because its gaming earnings are just a drop in the bucket compared to its total earnings.

NVIDIA is an AI company now

Gaming GPUs are taking a back seat

A graph showing NVIDIA revenue breakdown in the last few years. Credit: appeconomyinsights.com

NVIDIA’s gaming division had been its golden goose for decades, but come 2022, the company’s data center and AI division’s revenue started to balloon dramatically. By the beginning of fiscal year 2023, data center and AI revenue had surpassed that of the gaming division.

In fiscal year 2026 (which began on July 1, 2025, and ends on June 30, 2026), NVIDIA’s gaming revenue has contributed less than 8% of the company’s total earnings so far. On the other hand, the data center division has made almost 90% of NVIDIA’s total revenue in fiscal year 2026. What I’m trying to say is that NVIDIA is no longer a gaming company—it’s all about AI now.

Considering that we’re in the middle of the biggest memory shortage in history, and that its AI GPUs rake in almost ten times the revenue of gaming GPUs, there’s little reason for NVIDIA to funnel exorbitantly priced memory toward gaming GPUs. It’s much more profitable to put every memory chip they can get their hands on into AI GPU racks and continue receiving mountains of cash by selling them to AI behemoths.

The RTX 50 Super GPUs might never get released

A sign of times to come

NVIDIA’s RTX 50 Super series was supposed to increase memory capacity of its most popular gaming GPUs. The 16GB RTX 5080 was to be superseded by a 24GB RTX 5080 Super; the same fate would await the 16GB RTX 5070 Ti, while the 18GB RTX 5070 Super was to replace its 12GB non-Super sibling. But according to recent reports, NVIDIA has put it on ice.

The RTX 50 Super launch had been slated for this year’s CES in January, but after missing the show, it now looks like NVIDIA has delayed the lineup indefinitely. According to a recent report, NVIDIA doesn’t plan to launch a single new gaming GPU in 2026. Worse still, the RTX 60 series, which had been expected to debut sometime in 2027, has also been delayed.

A report by The Information (via Tom’s Hardware) states that NVIDIA had finalized the design and specs of its RTX 50 Super refresh, but the RAM-pocalypse threw a wrench into the works, forcing the company to “deprioritize RTX 50 Super production.” In other words, it’s exactly what I said a few paragraphs ago: selling enterprise GPU racks to AI companies is far more lucrative than selling comparatively cheaper GPUs to gamers, especially now that memory prices have been skyrocketing.

Before putting the RTX 50 series on ice, NVIDIA had already slashed its gaming GPU supply by about a fifth and started prioritizing models with less VRAM, like the 8GB versions of the RTX 5060 and RTX 5060 Ti, so this news isn’t that surprising.

So when can we expect RTX 60 GPUs?

Late 2028-ish?

A GPU with a pile of money around it. Credit: Lucas Gouveia / How-To Geek

The good news is that the RTX 60 series is definitely in the pipeline, and we will see it sooner or later. The bad news is that its release date is up in the air, and it’s best not to even think about pricing. The word on the street around CES 2026 was that NVIDIA would release the RTX 60 series in mid-2027, give or take a few months. But as of this writing, it’s increasingly likely we won’t see RTX 60 GPUs until 2028.

If you’ve been following the discussion around memory shortages, this won’t be surprising. In late 2025, the prognosis was that we wouldn’t see the end of the RAM-pocalypse until 2027, maybe 2028. But a recent statement by SK Hynix chairman (the company is one of the world’s three largest memory manufacturers) warns that the global memory shortage may last well into 2030.

If that turns out to be true, and if the global AI data center boom doesn’t slow down in the next few years, I wouldn’t be surprised if NVIDIA delays the RTX 60 GPUs as long as possible. There’s a good chance we won’t see them until the second half of 2028, and I wouldn’t be surprised if they miss that window as well if memory supply doesn’t recover by then. Data center GPUs are simply too profitable for NVIDIA to reserve a meaningful portion of memory for gaming graphics cards as long as shortages persist.


At least current-gen gaming GPUs are still a great option for any PC gamer

If there is a silver lining here, it is that current-gen gaming GPUs (NVIDIA RTX 50 and AMD Radeon RX 90) are still more than powerful enough for any current AAA title. Considering that Sony is reportedly delaying the PlayStation 6 and that global PC shipments are projected to see a sharp, double-digit decline in 2026, game developers have little incentive to push requirements beyond what current hardware can handle.

DLSS 5, on the other hand, may be the future of gaming, but no one likes it, and it will take a few years (and likely the arrival of the RTX 60 lineup) for it to mature and become usable on anything that’s not a heckin’ RTX 5090.

If you’re open to buying used GPUs, even last-gen gaming graphics cards offer tons of performance and are able to rein in any AAA game you throw at them. While we likely won’t get a new gaming GPU from NVIDIA for at least a few years, at least the ones we’ve got are great today and will continue to chew through any game for the foreseeable future.



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