The Integration of Web3 and AI: Building a Decentralized Intelligent Future

At a recent World Government Summit, a tech leader introduced the concept of "sovereign AI." This sparked discussions on which form of AI could best serve the interests and needs of the cryptocurrency community. The answer may be found in the combination of Web3 and AI.

A well-known blockchain expert discussed the synergy between cryptocurrency and AI in his article. He pointed out that the decentralization of cryptocurrency can balance the centralization tendency of AI; the transparency of blockchain can compensate for the opacity of AI; and blockchain technology also helps in the storage and tracking of data required for AI. This synergy permeates the entire industrial ecosystem of Web3+AI.

Currently, most Web3+AI projects are focused on leveraging blockchain technology to address the infrastructure issues within the AI industry, while a few projects concentrate on using AI to tackle specific challenges of Web3 applications. The main directions of the Web3+AI industry include:

1. Computing Power Layer: Assetization of Computing Power With the exponential growth in computing power demand for AI large model training, the market has encountered an imbalance in the supply and demand of computing power. Web3 technology provides a solution for this by establishing a distributed computing power network that utilizes idle mid-to-low-end hardware resources to create a Decentralization computing resource pool. This not only meets the diverse AI application needs but also significantly reduces computing power costs.

2. Data Layer: Data Assetization Data, as the core resource of AI, has always been a pain point in the industry regarding its acquisition and management. The combination of Web3 and AI provides a more economical and transparent solution for data collection, labeling, and storage. Through distributed networks and token incentive mechanisms, high-quality and extensive data can be acquired at a low cost while ensuring that the value of user data is reasonably compensated.

3. Platform Layer: Platform Value Assetization Platform projects aim to integrate various resources in the AI industry, including data, computing power, models, and developer communities. These platforms utilize Web3 technology to achieve efficient connection and allocation of resources, supporting the rapid construction and development of AI applications. Some projects also focus on addressing the AI black box problem, enhancing the transparency and credibility of model inference through cryptographic techniques.

4. Application Layer: AI Assetization At the application level, the combination of Web3 and AI is mainly reflected in two directions: first, AI as a participant in Web3, playing a role in decentralized games, trading, and prediction markets; second, creating scalable decentralized private AI, enhancing the transparency and credibility of AI through community governance.

Although the Web3+AI field is still in its early stages, its potential cannot be ignored. By combining the decentralization features of Web3 with the intelligent advantages of AI, we are expected to create products and services that are more valuable than traditional centralized AI. This integration could not only break the monopolistic pattern in the AI industry but also promote the concept of "co-governed AI," allowing humans to engage more deeply in the development of AI while maintaining a sense of awe and reducing unnecessary fears.

With the continuous advancement of technology and the emergence of more innovative projects, the Web3+AI ecosystem will continue to evolve. The development of this field is expected to bring us a more open, transparent, and intelligent digital future.