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The eponymous sign outside Epic headquarters in Verona, Wisconsin.

Source: Yiem via Wikipedia CC

Epic Systems, the largest provider of software for managing medical records, says a venture-backed startup called Particle Health is using patient data in unauthorized and unethical ways that have nothing to do with treatment.

Epic told customers in a notice on Thursday that it cut off its connection to Particle, hindering the company’s ability to tap a system with more than 300 million patient records. Particle is one of several companies that acts as a sort of middleman between Epic and the organizations — typically hospitals and clinics — that need the data.

Patient data is inherently sensitive and valuable, and it’s protected by the Health Insurance Portability and Accountability Act, or HIPAA, a federal law that requires a patient’s consent or knowledge for third-party access. One way Epic’s electronic health records (EHR) are accessed is through an interoperability network called Carequality, which facilitates the exchange of more than 400,000 documents a month, according to its website. Particle is a member of the Carequality network.

To join the network, organizations are vetted and have to agree to abide by clear “Permitted Purposes” for the exchange of patient data. Epic responds to requests for data that fall under the “Treatment” permitted purpose, which means the recipient is providing care to the person whose records they are requesting. 

Epic said in its notice on Thursday that it filed a formal dispute with Carequality on March 21, over concerns that Particle and its participant organizations “might be inaccurately representing the purpose associated with their record retrievals.” The company suspended its connection with Particle that day.

“This poses potential security and privacy risks, including the potential for HIPAA Privacy Rule violations,” Epic said in the notice, which was obtained by CNBC. 

In a blog post late Friday, Carequality said it takes disputes “very seriously and is committed to maintaining the integrity of the dispute resolution process as well as trusted exchange within the framework.” The organization said it can’t comment about the existence of any disputes or member activities.

Representatives from Epic and Particle didn’t respond to requests for comment. However, Particle published a blog post Friday evening and said it began “addressing this issue immediately” after Epic “stopped responding to data requests from a subset of customers” on March 21. Particle said in the post that a big challenge in such matters is that there is “no standard reference to assess the definition of Treatment.”

“These definitions have become more difficult to delineate as care becomes more complicated with providers, payers, and payviders all merging in various large healthcare conglomerates,” Particle wrote.

Epic, a 45-year-old privately held company based in Wisconsin, is the largest EHR vendor by hospital market share in the U.S., with 36% of the market, according to a May report from KLAS Research. Oracle is second at 25%, following the software company’s $28 billion purchase of Cerner in 2022.

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As of July 2022, Particle had raised a total of $39.3 million from investors including Menlo Ventures, Story Ventures and Pruven Capital, according to a release. The New York-based startup said at the time that its technology “uniquely combines data from 270 million plus patients’ medical records by aggregating and unifying healthcare records from thousands of sources.”

Epic said Particle introduced thousands of new participant connections to Carequality in October, and asserted that they fell under the treatment use case. In the following months, all of Particle’s participant organizations claimed a permitted purpose of treatment for their requests, Epic said. 

‘Non-treatment use case’

However, Epic began to notice some red flags. The company said it observed anomalies in the patient record exchange patterns, like requests for large numbers of records within a certain geographical region. Additionally, Epic said that the companies connected to Particle weren’t sending new data back from patients, which “suggests a non-treatment use case.” 

Epic and its Care Everywhere Governing Council, consisting of 15 industry representatives, evaluated Particle’s new participant connections and determined that organizations like Integritort, MDPortals and Reveleer, which acquired MDPortals last year, “likely didn’t conform to a Treatment Permitted Purpose,” the notice said.

Epic said it learned that another Carequality member was planning to file a dispute, alleging that Integritort was using the patient data to try and identify potential class action lawsuit participants. On March 28, Epic said it discovered that a participant called Novellia claimed it was requesting records under treatment, despite publicly advertising its product as a “personal health tool.”

Integritort, Reveleer and Novellia didn’t respond to requests for comment.

Epic said it filed a formal dispute with Carequality at the Governing Council’s recommendation. On April 4, Epic asked Particle to provide additional information to illustrate how its participants qualify for the treatment use case, according to the notice. 

Michael Marchant, director of interoperability and innovation at University of California Davis Health, serves as the chair of Epic’s Governing Council. He said it’s hard to know exactly why Particle might have provided these organizations with records, or whether it intentionally engaged in wrongdoing. But, he said, companies have to act responsibly even if pressured to deliver financial results.

“If they were selling to things that they knew were not treatment-related organizations in an effort to match VC funding or profit margins or revenue targets or what have you, then that would be really bad,” Marchant told CNBC in an interview.

In a statement on LinkedIn Wednesday, Particle founder Troy Bannister said Epic acted unilaterally, and that Particle has not seen “rationale, justification or official claims” surrounding these issues.

Bannister wrote that, to the company’s knowledge, “all of the affected partners directly support treatment.” He said these organizations pull data for care providers and share data back with the Carequality network. 

“While we continue maintaining our connection with Carequality, the ability for one implementor to decide, without evidence or even so much as a warning, to disconnect providers at massive scale, jeopardizes clinical operations for hundreds of thousands of patients as well as the trust that is so critical to a trust-based exchange,” Bannister wrote.

Bannister didn’t address Epic’s April 4 request for additional information.

The formal dispute process is still ongoing. Marchant, who also serves as the co-chair of an advisory council at Carequality, said it’s the first time in the network’s history that a complaint has gotten this far.

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Huawei ‘has got China covered’ if the U.S. doesn’t participate, Nvidia CEO tells CNBC

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Huawei 'has got China covered' if the U.S. doesn't participate, Nvidia CEO tells CNBC

If all the AI developers are in China, the China stack is going to win, Nvidia CEO tells CNBC

If the U.S. continues to impose AI semiconductor restrictions on China, then chipmaker Huawei will take advantage of its position in the world’s second-largest economy, Nvidia CEO Jensen Huang told CNBC Thursday.

“Our technology is a generation ahead of theirs,” Huang told CNBC at the sidelines of the Viva Technology conference in Paris.

However, he warned that: “If the United States doesn’t want to partake, participate in China, Huawei has got China covered, and Huawei has got everybody else covered.”

In the face of U.S. export curbs that restrict Chinese firms from buying advanced semiconductors used in the development of AI, Beijing has focused on nurturing domestic firms such as Huawei in a bid to build its own AI chip ecosystem.

Huawei CEO Ren Zhengfei this week told the People’s Daily Newspaper of the governing Communist party that Huawei’s single chip is still behind the U.S. by a generation.

“The United States has exaggerated Huawei’s achievements. Huawei is not that great. We have to work hard to reach their evaluation,” Ren said in comments reported by Reuters.

This is a developing news story and will be updated shortly.

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Nvidia’s first GPU was made in France — Macron wants the country to produce cutting edge chips again

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Nvidia's first GPU was made in France — Macron wants the country to produce cutting edge chips again

Jensen Huang, co-founder and chief executive officer of Nvidia Corp., left, and Emmanuel Macron, France’s president at the 2025 VivaTech conference in Paris, France, on Wednesday, June 11, 2025.

Nathan Laine | Bloomberg | Getty Images

French President Emmanuel Macron on Wednesday made a pitch for his country to manufacture the most advanced chips in the world, in a bid to position itself as a critical tech hub in Europe.

The comments come as European tech companies and countries are reassessing their reliance on foreign technology firms for critical technology and infrastructure.

Chipmaking in particular arose as a topic after Nvidia CEO Jensen Huang, who was doing a panel talk alongside Macron and Mistral AI CEO Arthur Mensch, said on Wednesday that the company’s first graphics processing unit (GPU) was manufactured in France by SGS Thomson Microelectronics, now known as STMicroelectronics.

Yet STMicroelectronics is currently not at the leading edge of semiconductor manufacturing. Most of the chips it makes are for industries like the automotive one, which don’t required the most cutting-edge semiconductors.

Macron nevertheless laid his ambition out for France to be able to manufacture semiconductors in the range of 2 nanometers to 10 nanometers.

“If we want to consolidate our industry, we have now to get more and more of the chips at the right scale,” Macron said on Wednesday.

The smaller the nanometer number, the more transistors that can be fit into a chip, leading to a more powerful semiconductor. Apple’s latest iPhone chips, for instance, are based on 3 nanometer technology.

Very few companies are able to manufacture chips at this level and on a large scale, with Samsung and Nvidia provider Taiwan Semiconductor Manufacturing Co. (TSMC) leading the pack.

If France wants to produce these cutting-edge chips, it will likely need TSMC or Samsung to build a factory locally — something that has been happening in the U.S. TSMC has now committed billions of dollars to build more factories Stateside.

Macron touted a deal between Thales, Radiall and Taiwan’s Foxconn, which are exploring setting up a semiconductor assembly and test facility in France.

“I want to convince them to make the manufacturing in France,” Macron said during VivaTech — one of France’s biggest tech events — on the same day Nvidia’s Huang announced a slew of deals to build more artificial intelligence infrastructure in Europe.

One key partnership announced by Huang is between Nvidia and French AI model firm Mistral to build a so-called “AI cloud.”

France has looked to build out its AI infrastructure and Macron in February said that the country’s AI sector would receive 109 billion euros ($125.6 billion) in private investments in the coming years. Macron touted the Nvidia and Mistral deal as an extension of France’s AI buildout.

“We are deepening them [investments] and we are accelerating. And what Mistral AI and Nvidia announced this morning is a game-changer as well,” Macron told CNBC on Wednesday.

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China’s racing to build its AI chip ecosystem as U.S. curbs bite. Here’s how its supply chain stacks up

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China's racing to build its AI chip ecosystem as U.S. curbs bite. Here's how its supply chain stacks up

Chip engineer handling a wafer.

Sinology | Moment | Getty Images

With the U.S. restricting China from buying advanced semiconductors used in artificial intelligence development, Beijing is placing hopes on domestic alternatives such as Huawei. 

The task has been made more challenging by the fact that U.S. curbs not only inhibit China’s access to the world’s most advanced chips, but also restrict availing technology vital for creating an AI chip ecosystem. 

Those constraints span the entire semiconductor value chain, ranging from design and manufacturing equipment used to produce AI chips to supporting elements such as memory chips. 

Beijing has mobilized tens of billions of dollars to try to fill those gaps, but while it has been able to “brute force” its way into some breakthroughs, it still has a long way to go, according to experts. 

“U.S. export controls on advanced Nvidia AI chips have incentivized China’s industry to develop alternatives, while also making it more difficult for domestic firms to do so,” said Paul Triolo, partner and senior vice president for China at advisory firm DGA-Albright Stonebridge Group.

Here’s how China stacks up against the rest of the world in four key segments needed to build AI chips. 

AI chip design

Nvidia is regarded as the world’s leading AI chip company, but it’s important to understand that it doesn’t actually manufacture the physical chips that are used for AI training and computing.

Rather, the company designs AI chips, or more precisely, graphics processing units. Orders of the company’s patented GPU designs are then sent to chip foundries — manufacturers that specialize in the mass production of other companies’ semiconductor products. 

While American competitors such as AMD and Broadcom offer varying alternatives, GPU designs from Nvidia are widely recognized as the industry standard. The demand for Nvidia chips is so strong that Chinese customers have continued to buy any of the company’s chips they can get their hands on.

But Nvidia is grappling with Washington’s tightening restrictions. The company revealed in April that additional curbs had prevented it from selling its H20 processor to Chinese clients.

Nvidia’s H20 was a less sophisticated version of its H100 processor, designed specifically to skirt previous export controls. Nevertheless, experts say, it was still more advanced than anything available domestically. But China hopes to change that. 

In response to restrictions, more Chinese semiconductor players have been entering the AI processor arena. They’ve included a wide array of upstarts, such as Enflame Technology and Biren Technology, seeking to soak up billions of dollars in GPU demand left by Nvidia.

But no Chinese firm appears closer to providing a true alternative to Nvidia than Huawei’s chip design arm, HiSilicon. 

Huawei’s most advanced GPU in mass production is its Ascend 910B. The next-generation Ascend 910C was reportedly expected to begin mass shipments as early as May, though no updates have emerged. 

Dylan Patel, founder, CEO and chief analyst at SemiAnalysis, told CNBC that while the Ascend chips remain behind Nvidia, they show that Huawei has been making significant progress. 

“Compared to Nvidia’s export-restricted chips, the performance gap between Huawei and the H20 is less than a full generation. Huawei is not far behind the products Nvidia is permitted to sell into China,” Patel said.

He added that the 910B was two years behind Nvidia as of last year, while the Ascend 910C is only a year behind. 

But while that suggests China’s GPU design capabilities have made great strides, design is just one aspect that stands in the way of creating a competitive AI chip ecosystem.

AI chip fabrication

To manufacture its GPUs, Nvidia relies on TSMC, the world’s largest contract chip foundry, which produces most of the world’s advanced chips.

TSMC complies with U.S. chip controls and is also barred from taking any chip orders from companies on the U.S. trade blacklist. Huawei was placed on the list in 2019.

That has led to Chinese chip designers like Huawei to enlist local chip foundries, the largest of which is SMIC.

SMIC is far behind TSMC — it’s officially known to be able to produce 7-nanometer chips, requiring less advance tech than TSMC’s 3-nanometer production. Smaller nanometer sizes lead to greater chip processing power and efficiency.

There are signs that SMIC has made progress. The company is suspected to have been behind a 5-nanometer 5G chip for Huawei’s Mate 60 Pro, which had rocked confidence in U.S. chip controls in 2023.  The company, however, has a long way to go before it can mass-produce advanced GPUs in a cost-efficient manner. 

According to independent chip and technology analyst Ray Wang, SMIC’s known operation capacity is dwarfed by TSMC’s. 

“Huawei is a very good chip design company, but they are still without good domestic chipmakers,” Wang said, noting that Huawei is reportedly working on its own fabrication capabilities. 

But the lack of key manufacturing equipment stands in the way of both companies.

Advanced Chip equipment  

SMIC’s ability to fulfill Huawei’s GPU requirements is limited by the familiar problem of export controls, but in this case, from the Netherlands. 

While Netherlands may not have any prominent semiconductor designers or manufacturers, it’s home to ASML, the world’s leading supplier of advanced chipmaking equipment — machines that use light or electron beams to transfer complex patterns onto silicon wafers, forming the basis of microchips.

In accordance with U.S. export controls, the country has agreed to block the sale of ASML’s most advanced ultraviolet (EUV) lithography machines. The tools are critical to making advanced GPUs at scale and cost-effectively. 

EUV is the most significant barrier for Chinese advanced chip production, according to Jeff Koch, an analyst at SemiAnalysis. “They have most of the other tooling available, but lithography is limiting their ability to scale towards 3nm and below process nodes,”  he told CNBC.

SMIC has found methods to work around lithography restrictions using ASML’s less advanced deep ultraviolet lithography systems, which have seen comparatively fewer restrictions.

Through this “brute forcing,” producing chips at 7 nm is doable, but the yields are not good, and the strategy is likely reaching its limit, Koch said, adding that “at current yields it appears SMIC cannot produce enough domestic accelerators to meet demand.”

SiCarrier Technologies, a Chinese company working on lithography technology, has reportedly been linked to Huawei.

But imitating existing lithography tools could take years, if not decades, to achieve, Koch said. Instead, China is likely to pursue other technologies and different lithography techniques to push innovation rather than imitation, he added.

AI memory components

While GPUs are often identified as the most critical components in AI computing, they’re far from the only ones. In order to operate AI training and computing, GPUs must work alongside memory chips, which are able to store data within a broader “chipset.”

In AI applications, a specific type of memory known as HBM has become the industry standard. South Korea’s SK Hynix has taken the industry lead in HBM. Other companies in the field include Samsung and U.S.-based Micron

“High bandwidth memory at this stage of AI progression has become essential for training and running AI models,” said analyst Wang.

As with the Netherlands, South Korea is cooperating with U.S.-led chip restrictions and began complying with fresh curbs on the sale of certain HBM memory chips to China in December. 

In response, Chinese memory chip maker ChangXin Memory Technologies, or CXMT, in partnership with chip-packaging and testing company Tongfu Microelectronics, is in the early stages of producing HBM, according to a report by Reuters.

According to Wang, CXMT is expected to be three to four years behind global leaders in HBM development, though it faces major roadblocks, including export controls on chipmaking equipment.

SemiAnalysis estimated in April that CXMT remained a year away from ramping any reasonable volume.

Chinese foundry Wuhan Xinxin Semiconductor Manufacturing is reportedly building a factory to produce HBM wafers. A report from SCMP said that Huawei Technologies had partnered with the firm in producing HBM chips, although the companies did not confirm the partnership.

Huawei has leaned on HBM stockpiles from suppliers like Samsung for use in their Ascend 910C AI processor, SemiAnalysis said in an April report, noting that while the chip was designed domestically, it still relies on foreign products obtained prior to or despite restrictions.

“Whether it be HBM from Samsung, wafers from TSMC, or equipment from America, Netherlands, and Japan, there is a big reliance on foreign industry,” SemiAnalysis said.

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