A Chinese AI system has shaken up global markets and intensified the US-China AI race. 

By delivering high performance at a fraction of the cost of its Western counterparts, DeepSeek has upended assumptions about AI development and raised pressing questions for global technology leaders.  

The rise of DeepSeek mirrors ChatGPT’s 2022 debut in redefining the AI landscape. But while previous models required immense computing power, DeepSeek has pioneered a cheaper, more efficient training method. 

It has also embraced open-source principles, allowing developers worldwide to build upon its technology - an approach that many hope will democratise AI development.  

“This actually is a kind of start of the Android era for larger AI models,” says Associate Professor Chang Xu from the University of Sydney.

DeepSeek’s efficiency also challenges the assumption that AI must be powered by expensive, high-end chips. 

By optimising its model architecture, it has delivered competitive performance without relying on cutting-edge hardware, a factor that has reshaped expectations about AI’s future accessibility.  

Despite its rapid adoption, DeepSeek has raised privacy concerns, particularly regarding its data storage policies. Australia’s science minister, Ed Husic, has urged caution. 

“I would be very careful about that, these type of issues need to be weighed up carefully,” he told ABC News.  

DeepSeek’s privacy policy states that user data - including email addresses, chat histories, and even keystroke patterns - is stored on secure servers in China. This has prompted scrutiny from cybersecurity experts, as well as restrictions from US officials. 

The US Navy has reportedly banned the app, citing “potential security and ethical concerns”, while the White House has begun assessing its national security implications.  

However, some argue that DeepSeek’s data practices are not vastly different from those of existing AI providers like ChatGPT or Gemini. 

DeepSeek’s launch sent shockwaves through the tech sector, triggering a sharp sell-off of AI stocks. 

Nvidia, the world’s leading AI chipmaker, lost nearly a trillion dollars in market value following the news. 

Despite this, the company acknowledged DeepSeek’s achievement, stating that “new models can be created using that technique, leveraging widely available models and compute that is fully export control compliant”.

DeepSeek’s founder, Liang Wenfeng, has long advocated for China to take a leadership role in AI development. 

“China’s AI can’t be in the position of following forever,” he said last year. 

“The real gap is the difference between originality and imitation … If this doesn’t change, China will always be only a follower.”  

His strategy - prioritising algorithmic efficiency over brute-force computing power - has disrupted traditional AI development methods. 

Some experts believe this could trigger a shift towards smaller, more efficient AI models, reducing reliance on massive data centres and high-end chips.  

“They have shaken the very foundation of the assumption that only the companies and countries with the fastest chips can dominate in AI,” says Professor Simon Lucey from the Australian Institute for Machine Learning.

Dr Armin Chitizadeh, an AI ethics researcher, has highlighted the broader implications of DeepSeek’s open-source approach. 

“It has introduced healthy competition, which benefits everyone,” he said. 

“This increased choice for consumers helps companies grow and innovate.”  

DeepSeek’s success underscores a broader shift in AI development. 

The US and China remain locked in competition, but DeepSeek’s efficiency and open-source model may lower the barrier for other countries and smaller players to enter the AI race.  

Meanwhile, privacy concerns and geopolitical tensions continue to loom over DeepSeek’s expansion. Whether it will emerge as a dominant AI platform or face regulatory roadblocks remains to be seen.  

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