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The shockwaves that followed the emergence of DeepSeek-R1, and the geopolitical tensions

A month ago, in January 2025, a promising Chinese AI startup, DeepSeek, released its inference model, DeepSeek-R1, causing a huge shock to the global AI industry. With two axes: ‘open source strategy’ and ‘efficient utilization of computing resources,’ DeepSeek provided this model with performance comparable to OpenAI’s o1 at about one-tenth the price, creating a new competitive landscape between closed and open models, and between the US and China. Throughout this time, we’ve learned a lot about the reactions from developers, users, and governments in these countries. Today, we want to bridge the gap and provide an overview of how key players, including European countries and Asian markets like Japan and Korea, are responding to DeepSeek’s move.

Responses of major countries: The strange coexistence of ‘AI nationalism’ and ‘open source AI’

After the DeepSeek incident, major countries around the world are responding with their own strategies.

The United States immediately began strengthening its own AI capabilities. President Trump announced the $500 billion ‘Stargate’ AI infrastructure plan right after taking office, declaring that he would make the United States the “world’s AI capital.” At the same time, he is withdrawing existing executive orders and further strengthening export controls on AI technology to China. Some in the U.S. Congress are even taking a hard-line stance that “Chinese AI should be completely blocked,” and the tone of ‘exclusive AI nationalism’ seems to be becoming more evident.

Europe, which has traditionally been at the forefront of ‘AI ethics and regulation,’ seems to be seeking a ‘deregulation’ and ‘openness’ path due to concerns that excessive regulation will lead to a decline in Europe’s AI competitiveness following the DeepSeek incident. At the recent Paris AI Summit, some EU leaders, including French President Macron, publicly supported a plan to grant flexibility to the new AI law in order to foster their own startups.

Asian countries such as Korea and Japan seem to be emphasizing ‘protection of their citizens’ and ‘technological sovereignty.’

The Korean government blocked key government officials from accessing DeepSeek immediately after the launch of DeepSeek, a preemptive response to growing concerns that sensitive information could be leaked due to Chinese AI models. Among private companies, major groups such as Hyundai Motor Company and Hanwha Group have banned the use of DeepSeek within their companies, and some are actively developing their own Korean AI platforms.

Japan has also begun reorganizing its AI strategy. As the impact of DeepSeek grew, the Japanese government announced that it would focus on security and ethics issues while establishing a basic plan for AI development and utilization. In addition, it began reviewing countermeasures that combine AI industry promotion policies with risk management, as well as energy policies to prepare for the surge in electricity demand in the AI ​​era.

While many countries are concerned about ‘protecting and fostering their own technologies’, they have one thing in common: they loudly advocate strengthening their own industries and ecosystems using ‘open source AI’.

I think the original core value of open source is ‘acceleration of innovation through collaboration without boundaries’. As has already been proven in the software industry, technological advancements are made by leaps and bounds when researchers and developers from around the world participate in an open environment.

The AI ​​field is no exception. Dr. Yann LeCun, chief scientist at Meta, also pointed out that DeepSeek’s success “doesn’t mean that China has surpassed the United States, but rather that the open source model is surpassing the closed model.”

However, can the current tense atmosphere, which can be called ‘AI nationalism,’ and ‘the development of the AI ​​ecosystem through open source AI’ coexist?

Global cooperation toward open source AI must be expanded even if it is difficult and challenging

In the dichotomous perspective of ‘open source vs. closed’ and ‘cooperation vs. self-reliance’, each country is faced with the dual task of developing its own technological capabilities while also participating in the formation of international norms. What we must clearly remember is that a nationalistic approach of confining AI capabilities within the country or investing only in strengthening its own AI capabilities will not only slow down the AI ​​innovation we desire, but also block the virtuous cycle of collaboration.

It has already been proven historically that faster and safer development is possible when talented people from all over the world gather their collective intelligence rather than when one organization or one country works in isolation.

In addition, openness and collaboration are not optional but essential for most countries except for the US and China.

If we compare the ‘scale of AI startup ecosystems’ in major countries around the world with the ‘level of AI research and development collaboration between countries’, we can see that countries such as the US and China have their own AI startup ecosystems of such a large scale that they can reap the benefits of ‘open source AI’ on their own.

However, even in countries like Korea and Japan in Asia that are already making large-scale investments in the growth of the AI ​​industry, individual AI startup ecosystems are limited in scale, and therefore, they cannot lead to innovation in domestic AI technology and growth of the industry with the catchphrase of ‘strengthening their own open source AI ecosystem’ and ‘nationalistic investments to independently develop AI capabilities and industries.

The reason France supports companies like Mistral while promoting itself as an ‘open source AI hub’ is because it realized that Europe must be included in a global cooperative network to become competitive. Ultimately, innovation is achieved in an open environment where collaboration is global, and security is also achieved through international cooperation. In an era where services developed by American AI startups today can be used by people in countries on the other side of the globe tomorrow, if we do not boldly abandon our AI nationalist perspectives and think about how to expand collaboration and cooperation with other countries and compete healthily, we will eventually become isolated and left behind. Korea, where I live, Japan, and countless other countries face the dual challenge of protecting AI sovereignty in terms of security and industrial competitiveness while at the same time not falling behind in an open ecosystem. However, we must not forget: knowledge shared across borders is the fuel for AI technology and industrial development. Looking back, deep learning research led by scholars from Canada and the UK also blossomed when capital from Silicon Valley in the US and data resources from various countries were combined. Without such global collaboration and value chains, would today’s AI innovation have been possible? Core tools such as Python, PyTorch, and TensorFlow, which are products of the open source movement, were created and widely used by developers around the world, not in a specific country, and have greatly accelerated the development of AI. If each country had controlled these knowledge and tools in a closed manner and had made it difficult for numerous developers around the world to collaborate, the speed of AI development would have been much slower than it is now, and the results would have been enjoyed only by some countries or regions.

Even amidst the current conflicts and concerns triggered by the DeepSeek incident and the competition for technological hegemony, we must not overlook the big picture of ‘cooperation for the common development of humanity.’ Now is the time when wisdom is needed to harmonize ‘global cooperation’ and ‘national interests.’

Today’s editorial is brought to you by Ben Eum, the Editor of Turing Post Korea

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