The Integration of AI and Web3: Building the Next Generation of Infrastructure

When a technological paradigm truly shifts, we often see the hype first, rather than the system. The current wave of AI is just like this. As an investor, I have always believed that focusing on the deepest transformative forces in the industry is far more valuable than chasing superficial narratives.

In the past year, various projects have been exploring the intersection of the real world and on-chain systems. However, one obvious trend is that regardless of the project direction, there is a need to integrate AI's collaborative logic to enhance competitiveness and efficiency. For example, RWA projects need to consider how to leverage AI for risk control optimization and dynamic pricing; consumers and DeFi projects require AI to accomplish user behavior prediction and strategy generation, among other tasks.

It can be said that whether it is asset digitization or experience optimization, these seemingly independent narratives will ultimately converge on the same technological logic: if the infrastructure does not possess the integration and carrying capacity of AI, it will not be able to support the complex collaboration of the next generation of applications.

The future of AI is not just about becoming more powerful and widely used; the real paradigm shift lies in the reconstruction of collaborative logic. Just like the early transformations of the internet, it was not because of the invention of DNS or browsers, but because it enabled everyone to participate in content creation and turn ideas into products, thus giving rise to an entire open ecosystem.

AI is also on this path: intelligent assistants will become co-creation partners for everyone, helping to transform expertise, creativity, and tasks into automated productivity tools, even enabling monetization. This is a problem that the current Web2 world finds difficult to solve, and it represents some underlying logic of the AI + Web3 track: making AI collaborative, transferable, and profit-sharing is the system that is truly worth building.

In this context, a project that attempts to systematically build the underlying operation of AI from the chain-level structure has caught my attention. This project is dedicated to creating an open, participatory ecosystem that everyone can own and benefit from. This is precisely the Achilles' heel of traditional public chains: they often serve developers in a one-sided manner, and the design of the token economy is mostly limited to Gas fees or governance, making it difficult to truly support the positive cycle of the ecosystem, let alone sustain the development of emerging tracks.

The design philosophy of this project hits my investment logic: true paradigm shifts do not lie in creating a single product, but in building a supporting system. It is precisely one of the most anticipated cases in my predictions.

The two co-founders of this project leave a deep impression. One is a young and accomplished university professor specializing in the field of AI; the other is an experienced Web3 investor with an astonishing level of self-discipline. Their dedication and execution are admirable, and they have shown me the potential of the project.

The project has achieved remarkable results in a short period of time: a large number of accounts have been activated on the test network, there are many data platform annotators, the clients served include several leading enterprises, and considerable revenue has been generated. All of this demonstrates the project's team's technical depth, background strength, and execution capability.

On this infrastructure chain, the project has gone deeper and more stable than most "AI narrative projects." It not only addresses the question of "who will do it," but also answers the challenge of "can it be done."

The core advantage of this project lies in its open, full-chain, standardized design philosophy. It supports deployment on any EVM-compatible chain while providing standard API interfaces that allow various systems to directly call its model services and complete on-chain settlements. Although this architectural design is extremely rare, it also faces challenges: the value of the infrastructure is not only in "what it can do", but more importantly in "who is willing to do what based on it".

The project has achieved key validation, providing services to several leading enterprises and addressing some of the industry's most challenging data demand issues. However, its long-term development still depends on the maturity and penetration of the entire Web3 AI sector.

As a unique presence in the current chain-level infrastructure track designed natively for AI, this project enjoys both "monopolistic advantages" and faces structural risks. It has the potential to define the industry benchmark for the entire Web3 × AI Infra, but it also needs to withstand rigorous verification over time and within the ecosystem.

For all builders and observers interested in this field, now is a rare opportunity window. Before the market has formed a clear consensus, you have already seen the existence, direction, and preliminary structure of this system. This is not a deterministic opportunity, but it is indeed a real beginning.

Not everyone can understand this opportunity, but if you have already realized this "thing that is ahead of consensus," then you are standing at a starting point with enormous potential. The key lies in how to seize this opportunity and get involved in this project that could change the landscape of the integration of AI and Web3.