Why Stopping China’s DeepSeek from Using US AI Technology Is Nearly Impossible
The global race for AI supremacy has intensified, with the United States and China leading the charge. Recently, concerns have surfaced about China’s DeepSeek, a rising AI innovator, potentially leveraging US AI advancements through a technique known as “distillation.” While US officials and tech leaders are sounding the alarm, preventing this practice may be far more complicated than it seems.
In this blog post, we’ll dive into why blocking DeepSeek from accessing US AI technology is so challenging, the implications of distillation, and the broader geopolitical tensions shaping the future of AI development.
What is AI Distillation, and Why Is It a Concern?
AI distillation is a process where a smaller or newer AI model learns from a larger, more advanced model. This allows the newer system to replicate the capabilities of the established one without the enormous costs of training from scratch. While this technique is widely used in the AI industry, it becomes controversial when applied across geopolitical boundaries.
Critics argue that distillation enables companies like DeepSeek to “piggyback” off the breakthroughs of US-based AI leaders such as OpenAI, potentially violating terms of service and intellectual property (IP) rights. This has sparked debates about fairness, competition, and national security in the AI landscape.
DeepSeek’s Rapid Rise and the Distillation Controversy
DeepSeek recently made headlines by releasing a cutting-edge AI model that rivals those developed by US tech giants—but at a significantly lower cost. Even more striking, DeepSeek made its code open-source, raising questions about how it achieved such rapid progress.
Many experts speculate that DeepSeek’s model may have been trained using outputs from US AI systems, effectively distilling knowledge from these models. This has led to accusations of IP misappropriation and calls for stricter regulations to protect US technological advancements.
The Challenge of Detecting and Preventing Distillation
One of the biggest obstacles in stopping distillation is the difficulty of detecting it. Popular AI models like OpenAI’s ChatGPT have hundreds of millions of users, making it nearly impossible to monitor every interaction. Additionally, open-source models such as Meta’s Llama and Mistral’s offerings can be freely downloaded and used in private data centers, further complicating enforcement efforts.
As Umesh Padval, Managing Director at Thomvest Ventures, explains:
“It’s impossible to stop model distillation when you have open-source models like Mistral and Llama. They are available to everybody, and users can easily access OpenAI’s models through customers.”
US Efforts to Curb AI Technology Transfer to China
The US government has taken steps to address the issue, with top officials expressing concerns about China’s use of US AI technology. Howard Lutnick, President Donald Trump’s nominee for Secretary of Commerce, recently vowed to impose restrictions on DeepSeek, calling its practices “nonsense” and promising rigorous enforcement.
Similarly, David Sacks, the White House’s AI and crypto czar, has raised alarms about DeepSeek’s alleged use of distillation techniques. However, implementing effective measures to prevent this practice is easier said than done.
The Role of Open-Source Models
Open-source AI models like Meta’s Llama and Mistral’s offerings have made advanced AI technology accessible to a global audience. While this democratizes innovation, it also creates challenges for enforcing IP protections. For example, Meta’s Llama license requires users to disclose if they use the model for distillation, but monitoring compliance is difficult.
DeepSeek has acknowledged using Llama for some of its models but has not clarified whether it used the model earlier in its development process. Meta has declined to comment on whether DeepSeek violated its terms of service, highlighting the complexities of enforcement.
Why Blocking DeepSeek Is So Difficult
1. Open-Source Accessibility
Open-source models are freely available, making it nearly impossible to control who uses them or how they are used. This creates a significant loophole for companies like DeepSeek to access and learn from US-developed AI systems.
2. Detection Challenges
With millions of users interacting with AI models daily, identifying instances of distillation is like finding a needle in a haystack. Small amounts of data from a larger model can significantly improve a smaller one, and such interactions are hard to trace.
3. Geopolitical Evasion Tactics
Chinese firms can bypass IP restrictions by using virtual private networks (VPNs) or other methods to mask their activities. For example, Jonathan Ross, CEO of AI computing company Groq, has blocked all Chinese IP addresses from accessing its cloud services. However, he admits this is not foolproof:
“That’s not sufficient, because people can find ways to get around it. It’s going to be a cat-and-mouse game.”
The Broader Implications for AI Development
The DeepSeek controversy underscores the growing tensions between the US and China in the race for AI dominance. It also highlights the challenges of regulating a rapidly evolving technology that thrives on open collaboration and innovation.
While the US government is exploring measures to protect its AI advancements—such as stricter export controls and know-your-customer requirements—these efforts may face significant hurdles. The Biden administration had proposed stricter regulations, but it remains unclear whether the current administration will adopt them.
READ MORE: DeepSeek AI: A Rising Star in the AI World – What You Need to Know and How to Use It
Final Thoughts
Stopping China’s DeepSeek from using US AI technology through distillation is a complex and multifaceted challenge. The accessibility of open-source models, the difficulty of detecting misuse, and the global nature of AI development make it nearly impossible to enforce strict controls.
As the AI race continues, the US will need to balance protecting its technological edge with fostering innovation and collaboration. In the meantime, the DeepSeek saga serves as a reminder of the high stakes and intricate dynamics shaping the future of AI
