The Evolution of AI in the Web3 Space: From Hype to Application

Since the emergence of ChatGPT at the end of 2022, the AI field has attracted considerable attention in the crypto community. The Web3 community has always maintained an open attitude towards the hype surrounding various concepts, especially with the limitless potential of AI technology. The AI concept initially surged in the crypto space in the form of the "meme coin craze," and subsequently, some projects began to explore its practical application value in the crypto domain.

This article will analyze the development of AI in the Web3 field, from early hype to the rise of current application projects, and explore industry trends in conjunction with cases and data. Our preliminary conclusions are as follows:

1. The era of AI meme coins has become a thing of the past, and the opportunities for speculative profits are over;
2. Some basic Web3 AI projects emphasize the benefits of decentralization for AI security, but users are more concerned about token returns and product experience.
3. Future investments in AI-related cryptocurrency projects should shift towards pure application or platform-based AI projects, which may become a longer-term investment hotspot after the hype around AI concepts.

The Development Path Differences of AI Between Web2 and Web3

AI in the Web2 World

AI in Web2 is mainly driven by tech giants and research institutions, with a relatively stable and centralized development path. Large companies train closed models, and the algorithms and data are not publicly available, leaving users with only the results and lacking transparency. This centralized control leads to AI decisions being non-auditable, with issues of bias and unclear accountability. Innovations in Web2 AI focus on enhancing the performance of foundational models and commercial applications, but the decision-making process is not transparent to the public.

Large AI models in Web2 still face two pain points: insufficient product experience and lack of precision in specialized fields. Many users opt for new AI products with lower barriers to entry and better experiences, and are willing to pay for them. At the same time, the information coverage of large models in segmented industries is not comprehensive or precise enough, which is another development direction for AI products.

AI in the Web3 World

Web3 integrates technology, culture, and community, attempting to move towards openness and community-driven initiatives. Web3's AI projects typically emphasize open-source code, community governance, and transparency and trustworthiness, striving to break the AI monopoly in a distributed manner. Some projects explore using blockchain to verify AI decisions or having DAOs audit AI models to reduce bias.

In an ideal scenario, Web3 AI pursues "open AI," allowing model parameters and decision logic to be audited by the community and incentivized through tokens for participation. However, in practice, the development of Web3 AI is still constrained by technical and resource limitations: building decentralized AI infrastructure is extremely challenging, and a few Web3 AI projects still rely on centralized models or services, merely integrating blockchain elements at the application layer. Most Web3 AI projects remain in the stage of conceptual hype.

Moreover, the differences in funding and participation models also affect the development of the two. Web2 AI is driven by research investment and product profitability, which is relatively stable. Web3 AI combines the speculative nature of the crypto market, often experiencing "boom" cycles that fluctuate with market trends: when concepts are popular, funds pour in; when they cool down, enthusiasm quickly declines. This makes the development of Web3 AI more volatile and narrative-driven.

We maintain a cautiously optimistic attitude towards the "decentralized AI network" proposition of Web3 AI. Currently, a more pragmatic approach is to explore some immediately implementable scenarios, such as embedding AI Agents in existing Web3 projects to improve efficiency, combining AI with other new technologies to develop new applications in the crypto industry, or focusing on providing customized AI services for the Web3 industry.

To be continued, the next article will review several waves of Web3 AI trends and comment on some representative projects among them.