In terms of timing, it doesn’t get much better than this. On 20 January 2025, with the world focused on Donald Trump’s inauguration, China’s DeepSeek quietly launched its low-cost, open-source, high-performance large language model, called R1. The capabilities of DeepSeek are reported to rival or even surpass OpenAI’s ChatGPT-4, and at a fraction of the cost (DeepSeek was reputedly built for US$6 million, however other estimates put it as high as US$1 billion). The impact was immediate: America’s Nasdaq plunged 3.1 per cent, while the S&P 500 fell 1.5 per cent.
DeepSeek’s emergence marks the latest flashpoint in US-China AI rivalry. Since 2017, technological competition between the two superpowers has intensified through tariffs, export controls, and market restrictions. The rapid development of Chinese artificial intelligence has reignited debates over US chip export controls. Critics argue these restrictions accelerate China’s domestic innovation, as evidenced by DeepSeek’s development. China has shown it can overcome barriers like limited access to top-tier chips by boosting efficiency or compensating for lower-quality hardware with quantity. This raises questions about the effectiveness and unintended consequences of US chip policies.
For Asia, the AI race is a double-edged sword. China’s low-cost, open-source model could empower emerging economies’ own AI innovation and entrepreneurship. It also pressures closed-source firms such as OpenAI to reconsider their stance. Meanwhile, the Trump administration has unveiled the $500 billion Stargate Project, the largest AI infrastructure initiative in US history. China, for its part, is projected to invest more than 10 trillion yuan (US$1.4 trillion) into technology by 2030. If managed well, these investments could spur job creation and foster global AI research collaborations between universities, AI labs, and startups.
However, US-China tech rivalry risks deepening global divides, forcing Asian nations (including Australia) to navigate growing complexities. How can Asian nations manage research partnerships with China without jeopardising collaboration with US institutions? And similarly, how can countries reliant on Chinese materials and exports avoid Chinese technologies? In 2023, South Korea, which is the world’s second-largest producer of semiconductors, became more dependent on China for five of the six critical raw materials it needs for chipmaking. Major firms such as Toyota, SK Hynix, Samsung, and LG Chem remain vulnerable due to Chinese supply chain dominance. Even the threat of disruption could discourage South Korea from fully siding with the United States in a tech war.
As part of its broader strategy to reduce partnerships with China, the United States has increased scrutiny of Chinese involvement in key industries, including Australia’s critical minerals sector.
As part of its broader strategy to reduce partnerships with China, the United States has increased scrutiny of Chinese involvement in key industries, including Australia’s critical minerals sector. Rare earth elements, lithium, and cobalt are crucial for high-performance semiconductors and batteries. With Trump’s new administration, Australia must balance China – its largest minerals export market and a key investor – with the United States, its primary security partner.
Also in the mix are the climate implications. Surging demand for AI data centres strains power grids and risks driving up emissions. According to the Institute for Progress, maintaining AI leadership will require the United States to build five-gigawatt clusters within five years. By 2030, data centres could consume 10 per cent of US electricity, more than double the 4 per cent recorded in 2023. China, home to the world’s largest 5G network and the second-largest data centre industry, faces similar challenges. Greenpeace East Asia estimates China’s digital infrastructure electricity consumption will surge by 289 per cent by 2035, pushing carbon emissions to 310 million tonnes.
Yet, if handled well, AI expansion could support energy transition. DeepSeek’s alternative approach – prioritising algorithmic efficiency over brute-force computation – challenges the assumption that AI progress demands ever-increasing computing power. This suggests that technological breakthroughs and environmental sustainability can coexist. Additionally, AI’s growing energy demands could drive investment in cheaper electricity sources, particularly in Asia, where green energy is increasingly viable.
Asian economies face many decisions in their AI journey. Importantly, they must weigh geostrategic considerations in working with Chinese technology and evaluate energy requirements. If market forces lead, the most cost-effective solutions will prevail, likely jeopardising US partnerships. If geopolitics and entrenched interests take over, a complex web of rules and exceptions will emerge. As always, the best path lies somewhere in the middle, likely through strengthened regional partnerships (eg. ASEAN). However, navigating these uncertainties will require more effective and adaptable strategies.
