China vs. US AI Competition: An Analysis of Data, Algorithms, and Computing

1. Data: China’s Dominance

Data is a core element of AI development, and China possesses a massive advantage in this area.
The personal information of 1.4 billion people is readily accessible, and the Chinese government possesses vast data that can be used for AI research through its strong data collection policies.
The amount of data accumulated from technologies like autonomous driving, CCTV, and facial recognition is at a level that is difficult for the U.S. to match.

Chinese AI experts account for approximately 49% of AI research and corporate positions in the U.S.
Through a strategy called the “Thousand Talents Plan,” China is attracting overseas talent and strengthening its own AI algorithm development capabilities.
- They are attracting core AI talent with offers of nine times the salary and three-year guarantees.
- This demonstrates China’s challenging strategy against the U.S. in algorithm development, a central part of the AI ecosystem.
Although the U.S. still leads in terms of algorithms, the gap is continuously narrowing due to China’s aggressive talent strategy and technology investment.

AI performance relies on computing power, and semiconductor technology plays a crucial role here.
China is focused on developing its own semiconductor technology through its “Semiconductor Leap Forward” policy.
The U.S. is dependent on GPU chip manufacturers like NVIDIA and has recently begun to strongly emphasize the physical AI domain.

Physical AI refers to robots, drones, and autonomous driving technology that operate in the real world, going beyond data and algorithm research.
China is already showing strong competitiveness in the physical domain by utilizing robots and drones.
- For example, mass manufacturing technology with high military applications.
In the US, Tesla is playing a key role in the physical AI field and is receiving national support in this area.

NVIDIA has proposed a new approach to AI learning by creating virtual worlds.
It provides platforms for testing robots and AI in virtual environments, seemingly intending to address data scarcity issues.
However, this may turn out to be a double-edged sword for the US, as it can also help China increase its learning efficiency.

Tesla currently represents physical AI, holding a significant position in autonomous driving and robotics technology.
The Trump administration and the US government are highly likely to push for support and deregulation for Tesla in order to maintain US AI technology hegemony.
There is concern about the fact that there are not many other companies representing physical AI competitiveness within the US besides Tesla.

< Summary >

In the data sector, China has an overwhelming advantage based on the existing data from its 1.4 billion population.
In the algorithm sector, the U.S. still leads, but China’s talent recruitment strategies and investment speeds are significant.
In the computing sector, the U.S. has a strong point in GPU technology, but the competition is expected to intensify depending on the pace of China’s semiconductor development.
In physical AI (robots, drones, autonomous driving), China is growing rapidly based on its manufacturing base, while the U.S. is forming its front centered around Tesla.
NVIDIA has proposed a new AI approach of virtual environment learning, but this could become a risk factor in the long run as it is also accessible to China.

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*YouTube Source: [이효석아카데미]

– [그냥효] Deepseek 논란, 하지만 진짜 승부는 여기에서 결정됩니다 [설특집 그냥효 2부]

The S&P 500 rose by 1.74%, and the Nasdaq increased by 1.65%.
Major indices are up 3-4% year-to-date.
On Friday, there was a decline in major tech stocks, including Nvidia, with market unease fueled by controversy over a CNBC video and DeepSeek.

DeepSeek is gaining attention for its cost-effectiveness, but long-term expansion of deep learning technology is expected to require more costs and investment.
The AI industry is poised for further expansion. Hardware and software companies like Nvidia are expected to see continued growth.
Due to trust issues and technological limitations of Chinese companies, US companies are likely to maintain their competitiveness.

Considering unemployment and housing cost data, inflation is likely to stabilize.
There is a high possibility of U.S. GDP growth reaching 2.5% by 2025.
The possibility of a recession this year is low at 5%, with a focus on growth rather than concerns about slowdown.

Interest rates are expected to move stably in the range of 4.25%-4.75%.
Despite high valuations, the growth potential of US companies is increasing their attractiveness.
Historically, considering the average 20-50% stock price increase in the two years after interest rate cuts, steady gains are possible over the next 1 to 1.5 years.

Any short-term corrections should be used as buying opportunities.
AI-related IT, semiconductor sectors, and tech stocks are major investment targets.
In particular, the sales and profit growth rates of hardware (e.g., Nvidia) and software companies due to AI technology development are expected to be rapid.

Compared to the 1995-2000 internet cycle, the AI market is also likely to grow rapidly in a similar form.
There is a possibility of forming another peak between 2028 and 2029.
High growth is expected for major AI-related companies and listed companies. In particular, attention should be paid to tech stocks such as Broadcom, Oracle, and Salesforce.

The U.S. stock market has potential for further gains despite recent adjustments and should be used as an investment opportunity.
The AI and IT industry is steadily growing, with exponential revenue and profit increases expected in related sectors.
Stable inflation, improved GDP growth, and stable interest rates make the U.S. economic outlook positive.
Long-term focus should be on a differentiated growth phase centered around tech stocks.