Summary of Key Points
Recently, a list of "young Chinese AI geniuses and billionaires" has sparked intense discussion: individuals born in the 1980s and 1990s with advanced education (such as Chen Tianshi and Yang Zhilin) have become part of the new generation of billionaires worth tens of billions thanks to prominent AI companies like Cambricon and DeepSeek. This represents a fundamental shift in the logic of wealth creation compared to the older generation of real estate or internet entrepreneurs. Netizens have debated topics such as whether education is useful, whether their wealth is a bubble or genuine, and why retail investors often suffer heavy losses, revealing the new rules and risks of wealth creation in the tech era, as well as the challenges faced by ordinary people in this context.
1. Has the "education is useless" argument completely changed? AI billionaires are all highly educated individuals
The wealthy from the real estate era (such as Li Ka-shing and Li Zhao-ji) typically had only primary school education and built their success on courage, connections, and resources, which led to the belief that "education was useless" along the southeastern coast of China ("teachers were not as valuable as tea egg sellers"). However, the AI era has turned this upside down:
- Three of the seven key figures on the list graduated from Tsinghua University (Yang Zhilin, Yan Junjie, Yu Hao), while others came from prestigious institutions like the University of Science and Technology of China and Zhejiang University; half of them hold doctoral or postdoctoral degrees (for example, Chen Tianshi has a Ph.D. in computer science, and Yang Zhilin holds a Ph.D. from Carnegie Mellon).
- They rely on technical patents and barriers to their success, not just sheer courage. Netizens joke, "Who would say education is unimportant now? In the AI world, it's embarrassing to be a boss without a degree from a top university."
Some even compare different fields, arguing that engineering is the key to rapid wealth creation, while majors in medicine and materials science do not see as significant growth in company value.
2. Can they afford 1 billion yuan in cash? Is the wealth of tech billionaires a bubble or a new form?
Netizens question whether these billionaires could actually afford 1 billion yuan in cash, reflecting skepticism about their wealth being merely nominal:
- Reasons for suspicion of bubbles: Many AI companies are still losing money (such as Cambricon), but their valuations have reached tens of billions due to "market dreams" (not based on current profits but on potential future growth). In contrast, real estate owners can liquidate their assets, and internet companies generate revenue from advertising. The true value of AI companies is not yet clear.
- Explanation for the new form of wealth: Observers argue that in the tech era, wealth is represented by "equity + ownership of technology," which essentially means the securitization of knowledge. Before going public, it's nominal wealth, but once listed, it can be converted into cash. The buyers of AI companies are often state-owned assets and industrial capital (the government provides funding, land, and orders to gain a competitive advantage in AI), so they are riding on national economic trends rather than ordinary business cycles.
However, there are risks: if the AI boom fades and they lose government or industrial support, and given the long payback period, their cash flow could be interrupted. Nevertheless, global competition in AI is fierce, so these risks are currently being overshadowed.
3. Retail investors suffer heavy losses, while geniuses become wealthy: Why doesn't tech wealth creation include ordinary people?
On one hand, geniuses are accumulating wealth in large numbers; on the other hand, retail investors are losing heavily (for example, some lost 2.1 million yuan due to speculative investments in AI stocks). The core reason is that the logic of wealth distribution has changed:
- Primary market vs. secondary market: Founders and early investors buy shares at low prices, while retail investors purchase shares that have been inflated after going public, resulting in losses when they try to sell them.
- Differences in wealth creation logic: In the internet era (e.g., Alibaba and Tencent), shareholders could benefit from continuous growth. However, AI companies' valuations are tied to distant future prospects (technology paths change frequently, and commercialization is uncertain), making them more suitable for risk capital investments rather than value investing by ordinary retail investors.
The result is a shift in wealth distribution from a more equitable model in the internet era to one where the founding teams and top investors take most of the benefits, leaving retail investors as mere "bidders" at higher prices.
4. Lessons for ordinary people: Understand the rules and don't follow trends blindly
This AI-driven wealth creation trend highlights the following lessons for ordinary people:
1. Education is still important: In the tech era, knowledge (especially in core technologies) is crucial for generating income.
2. Be cautious of bubbles: The wealth of AI billionaires represents "future money"; ordinary investors should avoid chasing high-priced AI stocks.
3. Choose the right field: If you can't succeed in AI, new consumer industries (such as Bubble Mart and Ba Wang Cha Ji) might be more suitable for starting a business from scratch.
4. View wealth rationally: Don't envy nominal wealth; true security lies in cash flow and liquid assets.
Senior AI observers even suggest that the current AI market is better suited for exiting investments rather than chasing rises and falls. Ordinary people need to stay clear-headed and not let the myth of quick wealth creation cloud their judgment.
This news article essentially illustrates a clash between different generations' approaches to wealth creation: from relying on courage and connections to focusing on technology and national economic trends, from cash assets to equity bubbles. Ordinary people must adapt to these new rules to protect themselves in this changing landscape.