Summary of Key Points
This article compares the different approaches to "attention" in the cryptocurrency (crypto) and artificial intelligence (AI) communities: In the crypto community, attention can be directly converted into asset prices and liquidity, rewarding those who create events and attract attention. In contrast, the AI community has evolved from an early phase where storytelling alone could secure resources, to a stage where attention must be supported by tangible achievements—whether it's through products (models/products) or the ability to make informed decisions (choosing the right direction), to building trust (being reliable and error-free), and ultimately by demonstrating practical results (changing industry practices).
1. Crypto Community: Attention as a Directly Monetizable Asset
The logic in the crypto community is simple: Attention = Liquidity = Money. For example, when someone like Sun Yuchen creates a sensation and becomes a hot topic of discussion, new users bring in capital to buy related cryptocurrencies, increasing trading activity (liquidity), which can drive up prices. Rising prices then attract more attention, creating a cycle.
Why does this work? The prices of many crypto assets are largely based on "consensus"—if people believe an asset is valuable, it becomes so. Creating events and attracting attention is the fastest way to reach this consensus. Therefore, the crypto community naturally rewards those who are proactive, willing to take risks, and can explain complex concepts in simple terms (for instance, explaining "decentralized finance" as "financial management without banks"), even if their ideas are controversial.
This doesn't mean the crypto community is all about speculation; there are also technical experiments. However, with highly volatile assets, the path to monetizing attention is much shorter than in other industries. A hot topic today can lead to price changes the next day.
2. AI Community: Attention from Unprotected to Requires Multiple Layers of Support
In the early days of AI (2023), it was similar to the crypto community. When GPT-4 emerged, people were wondering if AGI (Artificial General Intelligence) was possible and whether there was enough computing power. Those who could articulate ideas and access resources (such as GPUs, capital, or researchers) could gain money and opportunities. However, AI has a practical barrier: its effectiveness must be proven. Questions arose like, "Can the model actually work? Will people use the product? Will companies be willing to pay for it?"
As a result, the value of attention in the AI community has gradually become more structured:
- First Layer: Products (2024): Just claiming to understand AI is not enough; you need to present models, research papers, open-source projects, or products in use (e.g., tools that help designers).
- Second Layer: Decision-Making Ability (2025): With more products, you need to demonstrate the validity of your choices. For example, if you predicted the need for coding assistants in 2023 and they were developed in 2024, but then limitations in context management were discovered in 2025, your credibility is questioned.
- Third Layer: Trust (2026): As AI begins to be used in real work (e.g., data processing, process automation), concerns about reliability and accountability arise. You need a track record of stable performance (e.g., the product running smoothly for half a year).
- Fourth Layer: Results: Have your ideas or products truly changed the industry? For instance, if an open-source tool is widely adopted by companies and leads to further research, that demonstrates real influence.
The AI community can no longer tolerate those who only talk without action. You might make headlines, but the market will ask, "What have you actually achieved?"
3. The Evolution of Rewards in the AI Community
Over the past three years, the focus in the AI community has shifted with technological advancements:
- 2023: Who has cutting-edge intelligence? Resources like GPUs, training talent, and capital were scarce, so those who could access them were rewarded.
- 2024: Who can apply intelligence to practical problems? As open-source models became more accessible and computing costs dropped, the focus shifted to those who could integrate AI into real applications (e.g., financial tools, factory optimization).
- 2025: Who can make AI more reliable? The ability to connect AI with external data and manage its use became crucial, rewarding those who could optimize its performance.
- 2026: Who can integrate AI into production environments? Companies that use AI for core tasks value those who understand potential risks, manage permissions, and maintain logs (to prevent issues).
4. The Future of the AI Community: Four Types of People Will Be in High Demand
In the coming years, the focus in the AI community will be on specific skills:
1. People with Rare but Critical Insights: Those who make infrequent but impactful contributions, whose decisions are based on historical data and proven products.
2. Pragmatic Thinkers: AI is being applied in physical fields with high failure risks (e.g., manufacturing, healthcare, robotics). Those who understand the practical constraints will be valued.
3. Rule Designers: As AI systems need to collaborate, rules for interaction and accountability are essential. Those who can design these systems will be rewarded.
4. Feedback Mechanism Developers: AI needs to learn from experience, and those who can create systems that continuously improve will be highly sought after.
5. Fundamental Differences: Crypto vs. AI
The value of attention in these two communities is fundamentally different:
- Crypto Community: Attention is the goal; events alone can drive asset prices, regardless of practical outcomes.
- AI Community: Attention is a tool to amplify real results. While it may seem less exciting, as AI becomes more integrated, practical outcomes will become increasingly valuable.
In essence, the AI community is moving from conceptual speculation to practical application. The future winners will not be those who attract the most attention but those who can convert attention into tangible value.
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