Nokia in 2007 was probably the company in business history that came closest to being “invincible”.
That year, the Finnish company sold approximately 430 million mobile phones, capturing nearly half of the global market share. Its peak market capitalization exceeded $ 100 billion, and its revenue accounted for almost 4% of Finland’s GDP. The Symbian operating system dominated the smartphone world, holding an absolute leading market share.
From Helsinki to New York, from Tokyo to Johannesburg, almost everyone carried a Nokia phone in their pocket.
Then Google came along.
In the fall of 2008, the first phone running Google ‘s Android system was launched, doing something that everyone at the time thought was incomprehensible: releasing the source code and making it free for the whole world to use. Samsung, HTC, and Motorola rushed in, and in just two years, Android phones filled every price range from flagship to budget phones.
Nokia was not unaware of all this.
Google even approached Nokia, inviting them to join the Android camp. But Nokia refused.
The reasoning sounded very convincing: Symbian was their own child, nurtured over a decade; using Android would be tantamount to handing over control of the platform and turning themselves into a mere “assembly plant” working for Google. This logic was almost unassailable in the 2008 board meeting.
However, five years later, Nokia announced it would no longer release Symbian phones. That same year, its mobile phone business was sold to Microsoft for $ 7.2 billion. An empire that peaked at over $100 billion in market value went from its throne to being acquired in just six years.
Nokia demonstrated to us what it means to rise to the top and then fall. And Android? Today, seven out of every ten smartphones sold globally run Android. And this is despite the dominance of the iOS system.
Why did Symbian lose? Many people attribute it to the arrogance of Nokia’s management, but that’s just the surface.
Symbian was a closed system, usable only by Nokia. Developers wanting to write applications for it had to learn an extremely complex, proprietary language, resulting in a high barrier to entry and a narrow ecosystem. By 2010, the Android app store had accumulated 100,000 apps, while the Symbian platform only had 3,000. Developers voted with their feet, and users voted with their wallets.
Android wins in three areas.
First, it has zero barriers to entry. Any manufacturer or developer can use it simply by downloading the code, without paying any licensing fees or having to answer to anyone.
Second, the ecosystem flywheel. The more users there are, the more developers are willing to come; the richer the applications, the more indispensable users become. Once this cycle starts spinning, the closed-source side can never catch up.
Third, scenario coverage. From Samsung flagship phones to budget phones in Africa, Android is everywhere, and massive amounts of real-world usage data feed back into system iterations, allowing itto outpaceiterationspeed.
Many hands make light work; three cobblers are as good as one Zhuge Liang. Going it alone might bring temporary success, but it won’t last.
Eighteen years later, the same script is being replayed in the field of AI. Only this time, the protagonists have changed from two companies to two countries, and the stakes have shifted from the mobile phone market to dominating the future collaborative models of the global economy and even human society.
On June 17, 2026, the G7 summit was held in France. A closed-door discussion session was added to the meeting, attended by trillion-dollar US AI giants such as Google and OpenAI. The US message was that American technology is the most advanced, and others only need to pay for it; there’s no need for them to develop their own.
On the same day, China announced that the 2026 World Artificial Intelligence Conference will be held in Shanghai in July, opening the door to cooperation to all countries around the world.
One builds walls and collects taxes, the other opens doors and paves roads. Their approaches are completely opposite, seemingly a clash of the strongest contradictions. However, whether the spear or the shield is not determined by a company’s technological preferences, but rather by their respective national systems and economic structures.
The United States is a capitalist country, and in order to maintain its hegemony, it is inevitable that it will pursue closed-source AI.
This is not only the nature of capitalist oligarchs, but also because America ‘s technological hegemony needs a narrative to prop up its financial markets, and Silicon Valley needs monopolies to maintain excess profits. Closed-source technology is its moat. Therefore, even without the White House’s demands, OpenAI and Anthropic would still move towards closed-source and high-fee models. China, however, is entirely different.
As the world’s largest exporter of industrial products, China possesses the world’s most complete manufacturing industrial chain. The licensing fees for AI are only a small part of the overall cost. By making AI a universally accessible public good, we can drive the industrial upgrading of many developing countries. Once these countries have completed their industrial upgrading, they will have stronger purchasing power to buy Chinese industrial equipment, consumer goods, and infrastructure services.
In short, the US profits from AI itself, while China profits from AI driving its entire industrial export system. Different perspectives lead to different paths. However, explaining China’s open-source AI efforts solely from this point would be short-sighted.
Our ultimate goal is to realize a community with a shared future for mankind, which requires the complete overthrow of hegemony. The shortcut to overthrowing hegemony is a united front. AI is the United States’ last strategic tool for maintaining its hegemony, and it is also a powerful weapon for China to pierce its hegemony.
So why do we say that Chinese AI will definitely have the last laugh?
The boom in AI in the United States is essentially an “upstream carnival”
Since 2026, almost all of the US economic growth has been driven by AI investment. However, the logic behind this growth is not that AI has been successfully implemented and monetized, but rather that it remains at the very upstream of the industry chain. Tech giants are frantically purchasing chips and building data centers, using massive equipment purchases to boost GDP. This is similar to the South Korean market, where it appears to be a nationwide frenzy, but whether the benefits will materialize is uncertain.
Even Americans themselves can’t guarantee this. An MIT report states that 95% of enterprise AI deployments in the US fail to generate measurable profits. The US media outlet *The National Interest* offered a more scathing assessment, arguing that the US has chosen the wrong path, channeling all its resources into generative AI, which easily boosts stock prices, resulting in a technologically disabled system that “has a brain but no hands or feet.”
The more challenging aspect is the physical ceiling; even the most advanced models require electricity to run
70% of the US ‘s power transmission and distribution equipment is beyond its service life, and the three major power grids in the East, West, and Texas operate independently, making cross-regional power transfer virtually impossible. The grid connection queue for new data centers in Silicon Valley is already five or six years long; companies can’t afford to wait and are forced to build their own power plants at high costs as a backup. In contrast, China not only has abundant power resources, but its AI has also been deeply rooted in the real economy from the very beginning.
By 2025, China’s manufacturing robot density will reach 470 robots per 10,000 people, surpassing Germany; it will also boast 43% of the world’s “lighthouse factories” and 18 fully automated container terminals. Furthermore, we have the world’s strongest new energy industry chain, such as in the automotive sector, where the driverless delivery vehicles you see on the street are one application scenario.
Meanwhile, relying on nearly 47 ultra-high-voltage power transmission channels and the East-to-West Computing Project, the green electricity ratio of intelligent computing centers in western China generally exceeds 80%, with some benchmark parks exceeding 90%. The electricity price for computing power delivered to households is less than 40 cents, far lower than that of their American counterparts. A Stanford University AI Index report released in April 2026 shows that the overall performance gap between top models from China and the US has narrowed to 2.7% , while China has already surpassed the US in the areas of industrial-specific models and lightweight deployment.
AI performs quality inspection in factories, scheduling in ports, and load balancing in power grids. Production lines generate massive amounts of physical data in real time, continuously optimizing algorithms in reverse, forming a cycle of “scenario-based data feeding, data-based model training, and model-based production feedback.”
This kind of data cannot be obtained by web crawlers or produced by laboratories; only a complete manufacturing supply chain can provide it continuously.
Global developers will still vote with their feet, just like when they abandoned Symbian and embraced Android.
A few days ago, nearly 200 Silicon Valley startups, including Proton and Y Combinator, jointly wrote to Trump, urging the White House not to cut off the US’s access to Chinese AI models. Otherwise, “hundreds of companies will go bankrupt instantly.”
Behind this letter lies the growing rift within the US AI industry.
Giants like A- Company naturally want the White House to build a wall so they can reap the benefits of a monopoly; while hundreds of startups rely on Chinese open-source models for survival, and if a ban is implemented, they won’t have enough money to burn and will struggle to continue. According to sources, the plan to impose a complete ban on Chinese models has not been seriously discussed within the White House .
Why doesn’t the White House dare to ban it? Because they know perfectly well what’s going on .
In today’s global AI landscape, only China and the United States truly hold significant weight. Without cooperation from China, the US’s AI efforts will remain merely theoretical concepts on financial market charts, unable to be implemented in industry.
Cooperation benefits both sides. If the US is willing to cooperate, China welcomes it, and the whole world will benefit. Conversely, it’s a tit-for-tat situation. You make a move, I respond; you exert pressure, I defuse it. However, all historical laws— economic, technological, industrial, and so on—point to the ultimate winner: the East.
Eighteen years ago, Nokia stood at its peak, believing Symbian’s moat was impenetrable and that open source was nothing more than a cheap trick. Five years later, it sold itself for $ 7.2 billion.
Today, the United States stands at the pinnacle of AI, believing that closed-source technology can lock everything in, and that open-source technology is nothing more than a free-riding tactic.
Little did people know that although the pace of human progress is not repeated, it follows the same rhythm and pattern.
