In the realm of artificial intelligence (AI), recent developments in Europe and North America signal a shift in how state and private entities are collaborating to harness the power of technologyThe investments flowing from these regions represent not just a financial commitment but a comprehensive strategy to dominate global AI.

The rapid emergence of DeepSeek, a Chinese AI innovation, has understandably prompted reactions from Western nationsThis reaction is encapsulated in a statement from French President Emmanuel Macron regarding a substantial financial commitment aimed at bolstering France's AI sector.

According to a recent Reuters report, Macron announced that during the AI summit in Paris, France would unveil approximately €109 billion (around $119 billion) in private investments over the coming years, channeling these funds into various aspects of the AI industryAmong the notable investments, Canadian investment firm Brookfield is set to inject €20 billion ($22 billion) into French AI projects, while the UAE has hinted at an allocation of up to €50 billion ($55 billion) in the upcoming years for similar initiatives.

The French presidential administration revealed that a portion of the UAE's investment would specifically target the funding of a 1 gigawatt data centerAdditional reports indicate that a significant part of Brookfield's investments would also be funneled into the construction of data centers, emphasizing the growth of AI infrastructure.

Meanwhile, on January 23, 2025, an announcement was made regarding the United States initiating a project code-named “Stargate.” This extensive initiative, involving tech giants such as OpenAI, SoftBank Group, and Oracle, is slated for an investment of $500 billion over the next four years, aimed at establishing robust AI infrastructure to maintain the U.S.’s competitive edge in the global AI race

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While the overwhelming attention on the launch of DeepSeek might have diverted focus from this initiative, the underlying ambitions of both the U.S. and Europe in AI remain resolute.

The recent collaborations and commitments from both sides of the Atlantic highlight a notable trend: a state-driven approach to facilitate private investment into AI industries, thereby constructing a complete ecosystem that thrives on innovation and technological leadership.

Unlike the typical government-led funding model, the participatory "national system" approach seen in Europe and America synergizes public investment with private capital through policy guidanceMacron's recent declaration illustrates this, with over 70% of the €109 billion coming from private investments spanning diverse sectors from chip development (highlighted by companies like Soitec) to applications in medical AI, transportation, energy, and defense, while also addressing AI ethics and regulation frameworks.

In essence, the strategy revolves around leveraging tax incentives, data openness, and regulatory easing to attract private investment, all designed to forge a localized European AI ecosystem, thereby lessening reliance on U.S. technologiesFor instance, new legislation in France mandates the prioritization of public data access for domestic AI companies and plans to establish an “AI Sovereignty Fund” to invest directly in crucial startups.

On the American front, the ambitious $500 billion plan focuses on binding tech giants together: OpenAI for large model development, Oracle to provide cloud computing infrastructure, and SoftBank to spearhead AI chip design through its ARM architecture.

The strategic essence of this "big tech alliance" is clear; it aims to control the three core components of AI development: computing power (chips), algorithms (large models), and data (cloud platforms), thereby establishing a “U.S. standard” for global AI infrastructure

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A notable legislative push is underway, compelling all overseas AI enterprises using U.S. cloud services to undergo technological scrutiny, a move designed to fortify the U.S.’s leading position in the global AI landscape.

The shared theme between the U.S. and European “national systems” is the convergence of government leadership and private capitalBy spearheading policies and funds, these nations are invited to funnel significant investments into AI while simultaneously constructing a comprehensive value chain that encompasses everything from foundational research to commercialization.

DeepSeek's technological breakthrough has reverberated globally, showcasing the incredible potential of China's AI sector, particularly in vertical innovationThis transformation stems from two primary advancements: the autonomy in algorithms, which are developed entirely on domestic deep learning frameworks, and the rapid operationalization of these innovations, wherein numerous AI enterprises have swiftly adapted to market needsIn the pharmaceutical industry, for instance, DeepSeek collaborated with major companies such as Hengrui Medicine and WuXi AppTec to complete a comprehensive cycle from algorithm training to drug target verification in just three months.

Experts observe that while the U.S. currently maintains a lead in large model technologies, China's advancements in segment-specific fields like speech and video are noteworthy, allowing them to catch up rapidlyWith China's technological competencies reaching a competitive level against the U.S., it's evident that the former's innovations are invigorating the global AI race, akin to the catalyst effect of a “catfish” disrupting complacency.

However, AI is not solely defined by large models

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The DeepSeek instance reflects a successful “breakthrough at a single point,” yet China still faces systemic shortcomings within its AI industryIn light of providing structured competition from the West, it is imperative for China to establish a new model that synergizes government, market, and enterprise collaboration—a “new national system” to fortify its competitive stance.

Industry personnel argue that China's national system needs to commence with the establishment of a domestic AI computing network to achieve infrastructure autonomyThis can be expedited through the development of domestic GPUs and integrated memory computing chips, alongside collaborations with firms like Huawei and Cambricon to create a native computing cluster, thus breaking through existing chip constraintsAdditionally, the cultivation of deep learning frameworks should align closely with higher education institutions and companies to establish “open-source funds” that incentivize developers.

Furthermore, implementing pilot projects like “data sandboxes” across sectors such as healthcare and transportation can stimulate high-value data sharing while ensuring safetyConcurrently, replicating the “DeepSeek model” allows for an in-depth exploration of vertical scenariosThis model has already triggered a variety of effects, including cost efficiency and user engagement, boosted confidence, and fostered open-source ecosystems.

Experts anticipate that the AI industry will explore three promising directions: first, as AI 2.0 progresses past the current model cycle defined by large language models, emerging areas may include multi-modal, embodied intelligence, and spatiotemporal intelligence; second, the ecosystem surrounding AI large models may flourish, particularly in middle-tier and niche market segments; and third, the advent of edge AI agents, especially those that complement workflows and cater to personalized needs

In sectors like biomedicine (new drug development), renewable energy (smart grids), and agriculture (precision breeding), support funds can be established to prop up AI enterprises in creating collaborative laboratories, thus transforming technological advancements into tangible productivity.

Despite exhibiting remarkable progress in AI, China faces several challenges that include dependencies on foreign technologies in critical areas like AI chips, algorithm frameworks, and core software, which pose significant risks of disruptionMoreover, while there is a rapid growth in talent within AI, the country is still lacking high-level expertise, particularly in fundamental research and cutting-edge technologies.

With the European and American “national model” rapidly taking shape, Chinese enterprises are now confronted with intensified competition on the international stage.

The essence behind the Western approach to national systems is a distinctive usage of state power to consolidate market resources, a rare tactic in capitalist nationsAs China charts its path, there lies an urgent need to integrate its traditional strengths of centralized efforts with market dynamismThe triumph of DeepSeek indicates that by overcoming bottleneck challenges in core areas while stimulating enterprise innovation, China can absolutely forge a pathway in AI development that is driven by practical applications and market feedbackThe forthcoming competition in AI is not solely defined by algorithmic and chip rivalries; rather, it will culminate in a broader context of strategic national foresight and institutional resilience.

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