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AI's Next Chapter: Beyond Job Cuts, What's Coming?

Summary

Quick Abstract

Is the AI revolution stalling? This summary explores the current state of Artificial Intelligence, three years post-ChatGPT, and whether it's truly transforming our lives like the mobile internet did. We will examine the disconnect between AI's productivity gains and tangible benefits for everyday individuals, plus potential breakthrough directions.

  • Quick Takeaways:

  • AI's primary impact so far is on content production, not necessarily on broader societal needs.

  • Most people are not earning substantial money using AI tools. Few outside elite groups use it constantly.

  • Bosses see AI as cost-saving for businesses, while employees feel increased pressure without financial gain.

  • AI could break through by creating content that scores 80 points or higher, improving the efficiency in non-content fields, assisting scientific discoveries, and making progress toward robotic intelligence (GPR).

AI improves productivity, but needs to boost societal needs. The content sector is already saturated, so AI must expand into industrial and agricultural production or C-end services, like AI programming, to truly revolutionize our lives and the economy. The future hinges on AI's ability to solve pressing issues like managing logistics and advancing scientific research.

Lao Jiang discusses the current state of AI, reflecting on the AI revolution over the past three years since the emergence of ChatGPT 3.5. He believes AI is entering a phase of industry consolidation, similar to the mobile internet revolution a few years ago. While there is industry consensus on the potential of AI, a stable and profitable business model has not yet fully emerged.

AI Development: A Story of Isolation

Capital, Technology, and Media

The perception of AI has fluctuated within capital, technology, and media circles. Despite concerns about bubbles, there is a growing consensus that AI is a vital direction for future development. However, the impact on the average person is less obvious.

Limited Real-World Application

Despite high awareness, only a small percentage of people actively utilize AI tools consistently and profoundly change their lives. This usage is often concentrated among educated individuals in major cities.

The Challenge of Monetization

Survey Results: Productivity vs. Profit

A survey of 20 individuals revealed that while most recognized AI's productivity benefits, only a few could consistently earn a significant income (over 5,000 yuan/month) using AI. Some earned money by teaching others AI, while others leveraged AI in their existing industries.

Unsustainable AI Entrepreneurship

Many AI-based business ventures face problems with sustainability. Initial success driven by information gaps diminishes as awareness grows and competition increases. Simple AI applications become easily replicated.

Workplace Impact: Bosses vs. Employees

Bosses generally favor AI due to its cost-saving potential. AI tools can replace tasks previously done by specialized staff like translators or designers. However, employees often feel pressured to improve efficiency without seeing commensurate benefits, leading to a sense of being forced to "roll up".

The Need for Societal Impact

Productivity vs. Societal Needs

A key challenge for AI is that it has improved supply chain productivity but hasn't significantly enhanced overall societal needs in a way that's transformative. Unlike the Industrial Revolution, AI hasn't yet redefined how people live or broadly improved quality of life.

Lessons from the Industrial Revolution

The Industrial Revolution's impact stemmed not just from increased efficiency, but from fundamentally altering lifestyles. The population's increased life expectancy and other technological advancements created new demands.

The Mobile Internet Parallel

The mobile internet revolution also generated new needs, such as mobile gaming and on-demand services, driving economic development.

The Content Creation Bottleneck

The Problem with AIGC

AI is adept at generating content, but the current challenge is that the content market is already saturated with medium-to-low quality content. AI excels at producing average content (6-7 points out of 10), while high-quality, differentiated content still requires human creativity.

Limited Application in High-Quality Content

AI is mainly used for minor tasks like creating covers or subtitles, rather than core content creation. This limitation results in increased efficiency in mundane tasks, but it rarely benefits anyone beyond the high-level positions.

Future Breakthroughs for AI

Improving Content Quality

One direction is for AI to create higher-quality content (80+ points), filling the current scarcity of such content. To achieve this, AI needs to better understand user needs and provide more nuanced adjustments, allowing it to participate in higher-level content creation.

Expanding Beyond Content Creation

AI needs to broaden its impact beyond content production and integrate into wider production areas like industrial and agricultural production or C-end services. This would break the limitation of content consumption and satisfy the unlimited needs for material resources.

AI-Assisted Science

AI has significant potential in scientific fields like drug discovery, material science, and climate modeling. Scientific breakthroughs could address fundamental human needs and generate substantial demand.

Development of General Purpose Robotics (GPR)

Developing AI with "eyes, ears, hands and feet" would allow it to interact with the physical world and potentially replace many human jobs. This would require AI to develop a mature world model, understand the real world environment, and overcome numerous supervision challenges.

The Future: Focus on the Individual

In the coming months, Lao Jiang will release more videos addressing the future trends of AI development, including:

  • The impact of AI on individuals.

  • Job displacement risks.

  • Education and adaptation strategies for an AI-driven society.

  • The changing landscape of commercial competition.

  • AI's influence on the content industry.

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