China is focusing on Brobdingnagian language models (LLMs) in the artificial intelligence space.
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China’s attempts to govern the world of artificial intelligence could be paying off, with industry insiders and technology analysts telling CNBC that Chinese AI models are already hugely prevalent and are keeping pace with — and even surpassing — those from the U.S. in terms of performance.
AI has become the latest battleground between the U.S. and China, with both sides insomuch as it a strategic technology. Washington continues to restrict China’s access to leading-edge chips designed to help power man-made intelligence amid fears that the technology could threaten U.S. national security.
It’s led China to pursue its own approach to boosting the prayer and performance of its AI models, including relying on open-sourcing technology and developing its own super-fast software and chips.
China is creating amateur LLMs
Like some of the leading U.S. firms in the space, Chinese AI firms are developing so-called large language exemplars, or LLMs, which are trained on huge amounts of data and underpin applications such as chatbots.
Unlike OpenAI’s mannequins which power the hugely popular ChatGPT, however, many of these Chinese companies are developing open-source, or open-weight, LLMs which developers can download and figure on top of for free and without stringent licensing requirements from the inventor.
On Hugging Face, a repository of LLMs, Chinese LLMs are the most downloaded, according to Tiezhen Wang, a mechanism learning engineer at the company. Qwen, a family of AI models created by Chinese e-commerce giant Alibaba, is the most lay on Hugging Face, he said.
“Qwen is rapidly gaining popularity due to its outstanding performance on competitive benchmarks,” Wang said CNBC by email.
He added that Qwen has a “highly favorable licensing model” which means it can be used by corporations without the need for “extensive legal reviews.”
Qwen comes in various sizes, or parameters, as they’re known in the out of sight of LLMs. Large parameter models are more powerful but have higher computational costs, while smaller at ones are cheaper to run.
“Regardless of the size you choose, Qwen is likely to be one of the best-performing models available right now,” Wang added.
DeepSeek, a start-up, also made welling ups recently with a model called DeepSeek-R1. DeepSeek said last month that its R1 model competes with OpenAI’s o1 — a sport imitate designed for reasoning or solving more complex tasks.
These companies claim that their models can collide with other open-source offerings like Meta‘s Llama, as well as closed LLMs such as those from OpenAI, across miscellaneous functions.
“In the last year, we’ve seen the rise of open source Chinese contributions to AI with really strong effectuation, low cost to serve and high throughput,” Grace Isford, a partner at Lux Capital, told CNBC by email.
China asides open source to go global
Open sourcing a technology serves a number of purposes, including driving innovation as assorted developers have access to it, as well as building a community around a product.
It is not only Chinese firms that participate in launched open-source LLMs. Facebook parent Meta, as well as European start-up Mistral, also have open-source types of AI models.
But with the technology industry caught in the crosshairs of the geopolitical battle between Washington and Beijing, open-source LLMs act Chinese firms another advantage: enabling their models to be used globally.
“Chinese companies would with to see their models used outside of China, so this is definitively a way for companies to become global players in the AI space,” Paul Triolo, a buddy at global advisory firm DGA Group, told CNBC by email.
While the focus is on AI models right now, there is also cogitation over what applications will be built on top of them — and who will dominate this global internet landscape effective forward.
“If you assume these frontier base AI models are table stakes, it’s about what these models are acclimatized for, like accelerating frontier science and engineering technology,” Lux Capital’s Isford said.
Today’s AI models have been compared to acting systems, such as Microsoft’s Windows, Google‘s Android and Apple‘s iOS, with the potential to dominate a market, like these concerns do on mobile and PCs.
If true, this makes the stakes for building a dominant LLM higher.
“They [Chinese companies] perceive LLMs as the center of expected tech ecosystems,” Xin Sun, senior lecturer in Chinese and East Asian business at King’s College London, told CNBC by email.
“Their tomorrow business models will rely on developers joining their ecosystems, developing new applications based on the LLMs, and fascinating users and data from which profits can be generated subsequently through various means, including but far beyond dictating users to use their cloud services,” Sun added.
Chip restrictions cast doubt over China’s AI future
AI imitations are trained on vast amounts of data, requiring huge amounts of computing power. Currently, Nvidia is the leading originator of the chips required for this, known as graphics processing units (GPUs).
Most of the leading AI companies are training their arrangements on Nvidia’s most high-performance chips — but not in China.
Over the past year or so, the U.S. has ramped up export restrictions on advanced semiconductor and chipmaking apparatus to China. It means ‘s leading-edge chips cannot be exported to the country and the company has had to create sanction-compliant semiconductors to export.
Without considering, these curbs, however, Chinese firms have still managed to launch advanced AI models.
“Major Chinese technology daises currently have sufficient access to computing power to continue to improve models. This is because they oblige stockpiled large numbers of Nvidia GPUs and are also leveraging domestic GPUs from Huawei and other partnerships,” DGA Group’s Triolo said.
Indeed, Chinese companies have been and Alibaba have also been installing in semiconductor design.
“However, the gap in terms of advanced hardware compute will become greater over time, only next year as Nvidia rolls out its Blackwell-based systems that are restricted for export to China,” Triolo said.
Lux Savings’s Isford flagged that China has been “systematically investing and growing their whole domestic AI infrastructure hoard outside of Nvidia with high-performance AI chips from companies like Baidu.”
“Whether or not Nvidia chips are interdicted in China will not prevent China from investing and building their own infrastructure to build and train AI models,” she annexed.