Summary of Key Points
Professor Gao Bai uses the mourning phenomenon following the death of Zhang Xuefeng as a starting point to discuss the profound impacts of the AI revolution on education, employment, and social order. He highlights that AI not only changes the relationship between humans and tools (from humans commanding tools to AI participating in decision-making) but also drives the transformation of production methods towards "world models" (AI integrating into physical industries). There are significant differences in AI strategies between China and the United States: the U.S. focuses on developing general-purpose AGI, while China emphasizes practical applications in specific industries. The traditional diploma-based system of education is becoming obsolete, with the value of genuine skills taking precedence over prestigious university labels (such as 985/211). Ordinary people need to proactively adapt to these changes by mastering AI tools and delving into areas they passionate about; however, liberal arts subjects remain indispensable in the AI era.
I. The AI Revolution: Not Just an "Upgrade of Tools," but a Blurring of the Boundaries between Humans and Tools
Traditional tools (like computers) always required human instruction to function—people wrote the code, and humans made the decisions. However, AI is different:
- AI can make its own decisions: Professor Gao demonstrated how AI can generate 300,000 words of research material and over 300 pages of industry analysis, completing a task that would have taken two years in just a few days, thus increasing efficiency by hundreds of times.
- AI entering the physical world: AI has evolved from processing text (large language models) to performing practical tasks (world models). For example, autonomous driving uses digital twins for simulation before using real data for refinement. China's "AI + manufacturing" initiative aims to integrate AI into factories to optimize production processes.
However, AI can also create misinformation, but as technology improves, it will undoubtedly become a core tool for knowledge creation and industrial advancement.
II. Different Paths for AI in China and the U.S.
The approaches to AI development in China and the U.S. are distinctly different:
- The U.S.: General-Purpose AI (AGI): The U.S. strives to create an AI that can do everything, but whether a general model can be directly applied to manufacturing is doubtful, as each industry has its unique rules and expertise that outsiders often lack.
- China: Practical Applications First: China prioritizes applying AI to specific industries. To make AI useful in factories, the data from those industries must first be digitized, and then "world models" can be used for optimization, eventually leading to AI-driven intelligent production lines. This will create new job roles, such as technicians responsible for digital transformation.
III. The Transformation of Education: Diplomas Are Losing Their Value, and Genuine Skills Are the New Standard
In the past, a 985/211 degree was important when looking for a job, but this is no longer the case:
- Diploma devaluation is inevitable: After the Cultural Revolution, only 5% of students were admitted to elite universities; now, with nearly universal education, the value of diplomas as indicators of ability has diminished.
- A revolutionary shift in education: Shenzhen Polytechnic University collaborates with companies like BYD and Huawei to establish industry-specific colleges. The curriculum is developed by enterprises, engineers teach, and students gain practical experience directly in companies. Graduates can join R&D roles at BYD or even become managers. Large companies (such as Geely and ByteDance) recruit programmers from high schoolers, ignoring university diplomas.
- The future focuses on real skills: Skills like using AI tools and problem-solving abilities will be more valuable. Those who rely solely on test scores may fall behind.
IV. What Ordinary People Should Do
Ordinary people need to take the initiative:
- Learn AI tools: Use AI to improve efficiency in tasks such as writing reports and conducting research.
- Find something you love: Institutions like MIT prefer students who are deeply committed to their passions. If you enjoy programming, use AI to assist with projects and highlight your work during interviews.
- Don't wait for policies: Policies often lag behind technology, so take the initiative to learn and break through existing barriers.
V. Clarifying Misconceptions
Professor Gao addresses two common concerns:
- AI bubbles will burst? The internet bubble burst in 2000, but companies like Facebook and Google emerged afterward. AI investments may fluctuate, but technological progress is irreversible, and AI will become increasingly integrated into all sectors.
- Are liberal arts useless? Far from it. AI requires an understanding of human behavior and values. For example, designing products or formulating policies requires knowledge of social dynamics. Without humanities and social sciences, AI could become a soulless tool. Nobel laureates emphasize that each society must choose technology based on its own values, which relies on the contributions of liberal arts.
Conclusion: The Anxiety of Young People Is Rational; the Key is to Take Action
Professor Gao believes that the anxiety among young people is due to changing times—slower economic growth, AI-driven job changes, and the diminishing importance of diplomas. The key to adapting is to be proactive: use AI to enhance your skills, find your passion, and create your own opportunities.
In short, with the advent of AI, a diploma is no longer a guarantee of success; genuine abilities are what matter. Don't wait for others to offer you opportunities; take the initiative to learn AI and focus on what you love, and you can keep up with the times.