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On Mon, 26 Aug, 8:02 AM UTC
3 Sources
[1]
Nvidia's chips are banned in China -- but AI engineers have found a way around it
Artificial intelligence engineers in China are reportedly getting access to banned Nvidia (NVDA) chips through brokers despite U.S. export controls aimed at slowing the country's AI progress. Working with brokers, Chinese AI engineers are using servers that use Nvidia's AI chips without physically bringing the banned chips into the country, and some are doing so anonymously with cryptocurrency methods, the Wall Street Journal reported. Derek Aw, a former Bitcoin miner working with Chinese companies to access Nvidia's (NVDA) computing power, told The Journal he convinced investors in the U.S. and Dubai to help buy AI servers with Nvidia's H100 chips. Then, Aw's company placed over 300 of the servers into an Australian data center, which later started powering AI models for a Beijing-based company, according to The Journal. Despite U.S. efforts to tighten export controls on advanced chipmaking equipment sold to China, the country's AI firms have reportedly been able to access advanced chips from Nvidia through resellers, and even by renting Nvidia-powered servers from Google (GOOGL), Microsoft (MSFT), and other tech firms. Nvidia declined to comment. Nvidia has designed three chips to comply with existing export controls on China, including the H20. However, analysts at Jeffries said when the U.S. does its annual review of U.S. semiconductor export controls in October, "it is highly likely that" the H20 will be banned for sale to China. Meanwhile, the Biden administration was reportedly considering using an export control called the foreign direct product rule to prevent allies from selling advanced chipmaking equipment to China. Nvidia is also reportedly working on a version of its latest Blackwell AI platform for the Chinese market that will comply with U.S. trade restrictions. The U.S.-based chipmaker will reportedly work with a local distribution partner, Inspur, to launch and sell the chip, tentatively called the "B20," in China. Lawyers told The Journal that buyers, sellers, and brokers involved in accessing banned Nvidia AI chips are not breaking any laws, with cloud companies saying trade restrictions don't apply to accessing U.S. cloud services. However, the U.S. Commerce Department proposed a rule in January targeting "foreign malicious actors," aiming to ban them from accessing U.S. cloud computing infrastructure.
[2]
China's AI engineers are secretly accessing banned Nvidia chips
SINGAPORE -- Chinese artificial-intelligence developers have found a way to use the most advanced American chips without bringing them to China. They are working with brokers to access computing power overseas, sometimes masking their identity using techniques from the cryptocurrency world. The tactic comes in response to U.S. export controls that have prevented Chinese companies from directly importing sought after AI chips developed by U.S.-based Nvidia. While it is still possible for Chinese users to physically bring Nvidia's chips to China by tapping a network of gray-market sellers, the process is cumbersome and can't supply all the needs of big users. One entrepreneur helping Chinese companies overcome the hurdles is Derek Aw, a former bitcoin miner. He persuaded investors in Dubai and the U.S. to fund the purchase of AI servers housing Nvidia's powerful H100 chips. In June, Aw's company loaded more than 300 servers with the chips into a data center in Brisbane, Australia. Three weeks later, the servers began processing AI algorithms for a company in Beijing. "There is demand. There is profit. Naturally someone will provide the supply," Aw said. Renting far away computing power is nothing new, and many global companies shuffle data around the world using U.S. companies' services such as Google Cloud, Microsoft Azure and Amazon Web Services. However, those companies, like banks, have "Know Your Customer" policies that may make it difficult for some Chinese customers to obtain the most advanced computing power. The buyers and sellers of computing power and the middlemen connecting them aren't breaking any laws, lawyers familiar with U.S. sanctions say. Washington has targeted exports of advanced chips, equipment and technology, but cloud companies say the export rules don't restrict Chinese companies or their foreign affiliates from accessing U.S. cloud services using Nvidia chips. The Commerce Department in January proposed a rule that seeks to prevent malicious foreign entities from using U.S. cloud computing services for activities including training large AI models. U.S. cloud companies argue that the rule won't prevent abuse and could instead undermine customer trust and weaken their competitiveness. In platforms used by Aw and others, the billing and payment methods are designed to give the participants a high degree of anonymity. Buyers and sellers of computing power use a "smart contract" in which the terms are set in a publicly accessible digital record book. The parties to the contract are identified only by a series of letters and numbers and the buyer pays with cryptocurrency. The process extends the anonymity of cryptocurrency to the contract itself, with both using the digital record-keeping technology known as blockchain. Aw said even he might not know the real identity of the buyer. As a further mask, he and others said Chinese AI companies often make transactions through subsidiaries in Singapore or elsewhere. "Since late last year, there has been a significant increase in the number of Chinese customers on our platform," Aw said. "I often get asked if we have Nvidia's chips." Nvidia declined to comment. The company has said it complies with U.S. export controls and expects its partners to do the same. It is scheduled to report its quarterly earnings on Wednesday. Platforms such as Aw's have emerged in the past two years to take advantage of slower activity in the cryptocurrency field, which has freed up some computers previously used to mine digital currencies such as bitcoin. These platforms try to gather up computing power scattered across the globe and rent it out to AI developers. The service of selling scattered computing power is called a decentralized GPU model, referring to graphics-processing units. Nvidia's GPUs are widely used in AI applications and coveted on these platforms. Since the U.S. restricted advanced chips from being sold to China in 2022, more Chinese customers have been going to decentralized platforms for computing power, operators say. Joseph Tse, who until recently worked for a Shanghai-based AI startup, said his former employer turned to a decentralized GPU service after it found itself blocked from renting computing power from Amazon Web Services. The service arranged for more than 400 servers at a data center in California with Nvidia's H100 chips to help the company Tse worked for to train its AI model, he said. Tse said the service didn't differ much from cloud computing offered by the likes of Amazon or Google, but he said the risk was higher because the blockchain system might have flaws allowing code and data to be stolen. "Blockchain does protect the user's privacy, but it's therefore difficult to hold someone accountable if something goes wrong," Tse said. "But we didn't have a lot of options. We had to try everything to survive." One decentralized GPU provider with more than 40,000 chips in its network, io.net, advertises in its user guide that it doesn't impose know-your-customer restrictions. This "allows users to access GPU supply and deploy clusters in less than 90 seconds," it says. At an AI industry fair in Singapore in June, at least three decentralized GPU companies were touting platforms that provide untrammeled access to affordable Nvidia computing power around the world. All said they had customers from China. Startups and individual developers use the decentralized platforms to build and operate small AI applications that don't require heavy-duty computer power or split-second responses. However, decentralized networks typically can't train large AI models such as the one that powers ChatGPT. Those require thousands of chips to transmit data among themselves quickly. That issue is why operators such as Aw are building bigger clusters of processors in one place, often with the needs of specific customers in mind. Edge Matrix Computing, founded in 2022, is one company looking to build bigger chip clusters. EMC has connected more than 3,000 GPUs in its decentralized network, including Nvidia chips used for AI training that are subject to U.S. export controls. Users purchase access to the chips with EMC's tokens. EMC said it was soliciting investors to buy Nvidia H100 chips -- each of which can cost as much as a Cadillac sedan -- and assemble them in a data center for more intensive AI training. Users buying computing power in bulk could pay less than $2 for each hour of H100 use, it said. At a Senate committee hearing in July, Sen. John Kennedy (R., La.) argued that the Commerce Department has allowed Chinese users to exploit loopholes in chip-export restrictions. "It appears that the steady flow of advanced microchips into China continues. That flow must stop," Kennedy wrote in a letter to Commerce Secretary Gina Raimondo. At the hearing, Thea Kendler, assistant secretary of Commerce for export administration, said her department was closely tracking illicit procurement networks and "it's something we are cracking down on." Meanwhile, Aw is raising more money from a group of investors in Saudi Arabia and South Korea. They plan to build a cluster of Nvidia's latest Blackwell chips for another Singapore company with a Chinese parent. "No one is breaking the export controls," Aw said. "Legally speaking, they are Singapore companies."
[3]
Chinese companies using Amazon and other cloud for Nvidia's high-end AI chips: How it may not be US rules' violation - Times of India
Chinese companies linked to the government are reportedly employing cloud services offered by Amazon and other providers to access advanced US AI chips and capabilities, despite US export restrictions, which aim to curb the Chinese military's technological advancements. As per an investigation by news agency Reuters, at least 11 Chinese companies have been found seeking restricted US technologies via cloud platforms, with some explicitly naming Amazon Web Services (AWS). Shenzhen University spent 200,000 yuan ($27,996) on an AWS account to gain access to cloud servers powered by Nvidia A100 and H100 chips for an unspecified project, according to a March tender document. It got this service via an intermediary, Yunda Technology Ltd Co, the document showed, as per Reuters. AWS denies wrongdoing Meanwhile AWS has denied flouting US rules. "AWS complies with all applicable US laws, including trade laws, regarding the provision of AWS services inside and outside of China," a spokesperson for Amazon's cloud business was quoted as saying. Amazon has been found to be providing Chinese organisations access to not only advanced AI chips but also sophisticated AI models like Anthropic's Claude, which they wouldn't be able to access otherwise. Chu Ruisong, the President of AWS Greater China, publicly stated at a conference in Shanghai that their cloud platform, Bedrock, offers access to leading LLMs, including closed-source models like Claude 3. "Bedrock provides a selection of leading LLMs including prominent closed-source models such as Anthropic's Claude 3," Ruisong said at a generative AI-themed conference in Shanghai in May, referring to its cloud platform. How this is not a US rule violation Providing access to such chips or advanced AI models through the cloud, however, is not a violation of US regulations since only exports or transfers of a commodity, software or technology are regulated. The US government is actively working to close this loophole, with proposed legislation and regulations aiming to regulate remote access to US technology and require cloud service providers to verify and report users of large AI models. "This loophole has been a concern of mine for years, and we are long overdue to address it," said Michael McCaul, chair of the US House of Representatives Foreign Affairs Committee. Previously, it has been reported that Chinese companies have been using Microsoft cloud to access LLM models developed by ChatGPT creator OpenAI. The TOI Tech Desk is a dedicated team of journalists committed to delivering the latest and most relevant news from the world of technology to readers of The Times of India. TOI Tech Desk's news coverage spans a wide spectrum across gadget launches, gadget reviews, trends, in-depth analysis, exclusive reports and breaking stories that impact technology and the digital universe. Be it how-tos or the latest happenings in AI, cybersecurity, personal gadgets, platforms like WhatsApp, Instagram, Facebook and more; TOI Tech Desk brings the news with accuracy and authenticity.
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Chinese AI companies are finding ways to access Nvidia's high-end AI chips despite US export restrictions. They are using cloud services and brokers to obtain these chips, raising questions about the effectiveness of the export controls.
Chinese artificial intelligence companies have found innovative ways to access Nvidia's advanced AI chips, circumventing US export restrictions aimed at curbing China's technological advancement. This development has raised concerns about the effectiveness of the Biden administration's efforts to limit China's access to cutting-edge semiconductor technology 1.
One method Chinese firms are employing involves utilizing cloud services provided by tech giants like Amazon Web Services (AWS). By accessing these chips through cloud platforms, Chinese companies can bypass direct purchases and still benefit from the computational power of Nvidia's high-end AI processors 3.
Another strategy involves working with brokers and resellers who can procure the chips on behalf of Chinese firms. These intermediaries often operate in gray areas of international trade, exploiting loopholes in export regulations to supply the sought-after technology 2.
The ability of Chinese companies to access these chips despite restrictions highlights the challenges faced by US policymakers in enforcing export controls. It also underscores the global nature of the semiconductor supply chain and the difficulty in completely isolating one country from advanced technologies 1.
Nvidia, caught between US regulations and the demand from Chinese customers, has stated that it complies with all export control regulations. However, the company acknowledges the complexity of the situation and the potential for chips to reach restricted entities through various channels 2.
The access to these advanced chips allows Chinese AI firms to continue their research and development in areas such as large language models and other AI applications. This persistence in technological advancement could have significant implications for the global AI race and national security concerns 3.
The situation highlights the need for more comprehensive and nuanced export control measures. Policymakers must grapple with the challenge of balancing national security interests with the realities of a globalized tech industry and the rapid pace of AI innovation 1.
Reference
Tech giants Google and Microsoft are allegedly offering cloud services powered by Nvidia's AI chips to Chinese companies, potentially circumventing US export restrictions. This development raises questions about the effectiveness of the ban and its impact on global AI competition.
10 Sources
Chinese companies and researchers are turning to cloud services provided by Amazon, Microsoft, and Google to access high-end US chips for AI development, potentially circumventing export restrictions.
16 Sources
Despite US export restrictions, China continues to access NVIDIA's AI chips through smuggling and discounted rental services, highlighting the challenges in enforcing tech export controls.
2 Sources
Recent reports reveal that renting NVIDIA's AI GPUs is significantly less expensive in China compared to the United States, raising questions about global AI chip accessibility and market dynamics.
4 Sources
Chinese authorities are advising local companies to prioritize domestic AI chips over NVIDIA's, despite challenges in transitioning from the U.S. tech giant's products. This move reflects China's push for technological self-reliance amidst ongoing trade tensions with the United States.
3 Sources
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