Summary of Key Points
This article discusses the chain reactions brought about by the development of AI, using specific examples such as potential declines in Tencent's gaming revenue and negative cash flow in Google's financial reports. It also analyzes three core underlying trends: AI is quietly eroding the markets for traditional businesses like gaming and advertising; Technology companies rely on “valuation magic” to maintain high growth expectations; The United States intends to turn AI into a long-term profit-making venture, but its pace has been disrupted by China’s rapid progress in large-scale AI models.
Detailed Explanation
1. How Do Large-Scale Models Take Money Away from Gaming and Advertising?
The article explains the possible decline in Tencent's gaming revenue with practical reasons:
- Students Turning to Self-Created Games: High school and middle school students are now using tools like VIBE CODING to create simple games for their peers, finding this interaction more engaging than purchasing games from big companies like Tencent or MiHoYo. As a result, money is flowing from major game publishers to these smaller, self-created communities.
- Adults Prefer More Prestigious Investments: For the same amount of money, spending on large-scale AI models (e.g., for chat or exploration functions) is seen as more advanced and desirable, rather than on games.
- Ad Business Displacement by AI: In the past, people used platforms like Baidu or Google to search for information, which often displayed numerous ads. Now, with services like KIMI and DouBao providing pre-organized answers, advertisers find that fewer people are clicking on their ads, leading to a decrease in spending—thus, Google’s ad revenue is being impacted by its own AI investments.
This is similar to how Meituan overtook Kangshifu (taking over the convenience food market); who would have thought that large-scale AI models would become the threat to traditional businesses?
2. Google’s Dilemma of Protecting Both Big and Small Businesses
Google’s financial report reveals a contradiction:
- High Costs for AI: The company is spending heavily on AI, with negative cash flow. With over $200 billion in assets, it can only sustain this situation for two years, and yet no stable source of revenue has been found for AI.
- Erosion of Profitable Business: Its own ad business, which was once its main profit generator, is being impacted by AI, as users avoid using the search engine, resulting in fewer ads.
This dilemma is akin to the classic question in TV dramas about whether to prioritize a new (highly valued) business or a traditional one (lowerly valued). No one can guarantee the short-term outcome.
3. Capital’s “Valuation Magic”: Turning Cash into Revenue by Doubling Valuations
Capital has a simple strategy:
- Low Valuation for Mature Businesses: Traditional businesses like advertising are typically valued at around 10 times their revenue.
- High Valuation for Innovative Businesses: Innovative AI companies can be valued at 100 times their revenue.
- Mutual Business Acquisitions to Boost Valuations: Companies exchange cash for each other’s assets, turning cash from an “asset valuation” (low value) into a “revenue valuation” (high value). This increases valuations and allows them to raise funds more easily than through traditional methods of making money.
4. The Technology Version of “Keeping the Enemy at Bay”: The United States Hopes for a Slow Adoption of AI, but China is Catching Up Quickly
American technology companies prefer a delayed and costly adoption of AI:
- Long-Term Profit Potential: The longer the story around AI continues, the higher its valuation, allowing capital to earn more.
- China’s Rapid Progress Disrupts Plans: Companies like OpenAI and Anthropic restrict Chinese users from using their latest versions, accusing Chinese models of “copying”. In reality, this is a fear that China will accelerate the adoption of AI, disrupting their plans.
This is similar to the situation with the stranded Philippine ship: instead of towing it away, the US used it as an excuse to strengthen its presence in the South China Sea. The US’s narrative around AI has led to China becoming a formidable competitor, much like how Li Chengliang’s efforts to nurture Nurhaci turned out against him.
5. The Underlying Differences in Consumption Between China and the United States
Why is US consumption higher than China’s?
- Global Support for US Consumption: World-class consumers are willing to pay high prices for things like World Cup tickets, while local workers cannot afford them. American tech startups can afford luxury through financing.
- China’s Self-Sustained Consumption: Chinese consumers have to earn their money, so they are more frugal with it.
The US’s narrative of democracy, freedom, and technology is difficult to refute in the short term and attracts global resources. China’s focus on developing its own tech capabilities has become a challenge for the US, as it intended to use AI as a tool for its own growth but now faces a strong competitor.
This article explains the impact of AI on traditional businesses, capital strategies, and international competition in simple language, making it engaging like a story, yet it reflects real business and political dynamics.