Recently diving deep into AI applications, the increasingly obvious feeling is: this has long surpassed the scope of a simple "efficiency tool" and is actually redefining the global resource allocation and power structure.

When top-tier models can be used to train the next generation of more powerful models, the growth of leaders will accelerate exponentially. This is not just a matter of "leading a bit," but an overwhelming advantage created by a "technological gap." The result is harsh: ordinary people find it very difficult to develop truly independent technical capabilities.

Under this logic, the landscape of the digital world will become more and more centralized. Those who have already mastered core computing power and data will continue to expand their advantages through self-reinforcing mechanisms. In relation to the Web3 ecosystem, this trend is precisely the core issue that decentralization aims to address: how to prevent power and resources from becoming overly concentrated in a few nodes?

Perhaps this is also why we need to think more about diverse participation mechanisms and more transparent rules. In an era where AI empowers everything, if all intelligent tools are controlled by a very small number of people, we will face an unprecedented imbalance of power.