In a bid to restrict China’s AI progress, the US may implement a proposal asking cloud companies to reveal client information using their platforms to develop AI applications.
Amid the war for global dominance in the AI era, the US administration is considering making it mandatory for prominent global cloud services providers — such as Amazon, Google, and Microsoft — to reveal details about the customers developing AI applications on their platforms. Thin Client Desktop
The move, if implemented, will demand the cloud companies to invest in setting up mechanisms to collate the required information and share it with the US administration. The proposed policy change is seen to be targeting Chinese companies that can use cloud companies to train their large language model.
“We want to make sure we shut down every avenue that the Chinese could have to get access to our models or to train their own models,” US Commerce Secretary Gina Raimondo said in an interview with Bloomberg recently.
“With the new proposal, it is trying to pre-empt the usage of cloud services by disclosing the transactions, including the details of client and IP addresses for AI model training services and potentially restricting access to persons that might use it in a manner not in alignment with directives from US government,” said Akshara Bassi, senior analyst at Counterpoint Research.
The proposal is in line with the several steps taken by the Biden administration to curtail China’s progress in AI. The US introduced a chips ban in October 2022, barring the export of AI chips, including Nvdia’s AI chips, to China. A year later, it followed this by expanding the ban on chip manufacturing equipment to close any loophole that weakened the original ban. This ban addressed the hardware components of an AI system, including the logic and memory chips and manufacturing equipment for opening a new foundry.
“Companies circumvented it by either adopting lower compute hardware to train their AI models or leasing AI cloud services through major cloud providers that offer the latest chips – [Nvdia’s] H100/A100 for AI model training. The frequently opted cloud providers were US-based as they currently have access to the majority of the existing AI infrastructure globally that is required to train and build AI models, with Microsoft, Google, and Amazon leading the cloud services catering to AI workloads,” Bassi explained.
The US government had also asked the Commerce Department in October last year to demand the cloud companies to reveal the client names that used their cloud infrastructure.
The proposed change can restrict the pace of innovation in the Chinese AI ecosystem as the Chinese AI developers may be subjected to greater scrutiny by the US Government.
“On the other hand, for local alternatives like Baidu ERNIE, Alibaba Tongyi Qianwen, Tencent Hunyuan, Huawei Pangu, Zhipu GLM, and Baichuan, this becomes important leverage for them to focus on their innovation despite the performance gap. It will also force Chinese vendors and enterprises to further prioritize localization, accelerating the evolution of AI software and hardware ecosystem in the long run,” said Charlie Dai, Vice President and Principal Analyst at Forrester.
The restrictions may have implications for the global AI ecosystem as well. “In general, this will cast a shadow over the global AI ecosystem. Firstly, foreign companies, particularly those from China, may face greater scrutiny and oversight from the US government. This increased attention could lead to delays, additional costs, and potential restrictions on the development and deployment of AI applications,” Dai said.
In addition, the requirement to disclose sensitive information about technology, data usage, and business operations can raise significant concerns about IP protection. Companies may be hesitant to share proprietary information that could be misappropriated or used by competitors.
“Thirdly, greater transparency could expose sensitive data and increase the risk of data breaches or other security incidents. This is particularly concerning for enterprises handling sensitive customer or business data. Finally, regulatory uncertainty can dampen investment in AI research and development, particularly if companies fear that today’s acceptable practices might become subject to new restrictions tomorrow,” explained Dai from Forrester.
Enterprise Cloud Computing For the US cloud companies, it would mean additional expense as well as compliance requirements to collect as well as store information about their customers.