Author: Guotian Laboratory
Introduction
Since ChatGPT made its debut at the end of 2022, the AI sector has been highly sought after in the cryptocurrency field. The WEB3 nomads have long accepted the idea that "any concept can be hyped," not to mention AI, which has limitless narrative contexts and application capabilities in the future. Therefore, in the crypto circle, the AI concept initially exploded in popularity as a "Meme craze" for a while, and then some projects began to explore its actual application value: What new practical applications can cryptocurrency bring to the rapidly advancing AI?
This research article will describe and analyze the evolutionary path of AI in the Web3 field, from the early hype waves to the current rise of application-based projects, and will incorporate cases and data to help readers grasp the industry context and future trends. Let's throw out an immature conclusion right from the start:
01
The era of AI memes is already in the past; what should be cut and what should be earned remain as eternal fragments of memory.
02
Some basic WEB3 AI projects have been emphasizing the benefits of "decentralization" for AI security, but users are not buying into it much. What users care about is whether "tokens are profitable" and "whether the product is user-friendly."
03
If you want to invest in AI-related cryptocurrency projects, the focus should shift to pure application-based AI projects or platform-based AI projects (which can concentrate many tools or agents that are easy for C-end users to use). This could be a longer-term wealth hotspot after the AI Meme.
Differences in the development paths of AI in Web2 and Web3
AI in the Web2 World
In the Web2 world, AI is mainly driven by tech giants and research institutions, with a relatively stable and centralized development path. Large companies (such as OpenAI and Google) train closed black box models, where algorithms and data are not disclosed, and users can only use the results, lacking transparency. This centralized control leads to AI decision-making being non-auditable, with issues of bias and unclear accountability. Overall, AI innovation in Web2 focuses on improving the performance of foundational models and commercial applications, but the decision-making process is opaque to the public. This opacity has led to the emergence of new AI projects like Deepseek in 2025, which seem open source but are actually 'fishing in a barrel'.
In addition to the opaque flaws, large AI models in WEB2 also have two other pain points: insufficient user experience across different product forms and inadequate precision in specialized sub-sectors.
For example, if you want to create a PPT, an image, or a video, users will still look for new AI products with a lower entry barrier and a better user experience to use, and they are willing to pay for it. Currently, many AI projects are trying to create no-code AI products to lower the entry barrier for users even further.
For many WEB3 users, there is often a sense of helplessness when using ChatGPT or DeepSeek to obtain information about a particular crypto project or token. The data from large models still cannot precisely cover the detailed information of any niche industry in this world. Therefore, another development direction for many AI products is to achieve the most in-depth and accurate data and analysis in a specific niche industry.
AI in the Web3 World
The WEB3 world is a broader concept centered around the cryptocurrency industry, integrating technology, culture, and community. Compared to WEB2, WEB3 attempts to move towards a more open and community-driven approach.
With the decentralized architecture of blockchain, Web3 AI projects often claim to emphasize open-source code, community governance, and transparency, hoping to break the traditional monopoly of AI by a few companies in a distributed manner. For example, some projects explore using blockchain to verify AI decisions (zero-knowledge proofs ensure the credibility of model outputs) or have DAOs review 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, while incentivizing developers and users to participate through a token mechanism. However, in practice, the development of AI in Web3 is still constrained by technical and resource limitations: building decentralized AI infrastructure is extremely challenging (training large models requires massive computational power and data, yet no Web3 project has funding that comes close to that of OpenAI), and a few projects claiming to be Web3 AI still rely on centralized models or services, only incorporating some blockchain elements at the application layer. Among these, some Web3 AI projects are relatively reliable and have genuine development applications; however, the vast majority of Web3 AI projects are either pure memes or memes masquerading as real AI.
In addition, the differences in funding and participation models also affect the development paths of the two. Web2 AI is typically driven by research investment and product profitability, with a relatively smooth cycle. In contrast, Web3 AI combines the speculative nature of the cryptocurrency market, often experiencing "boom" cycles characterized by drastic fluctuations in market sentiment: when the concept is hot, funds flood in, driving up token prices and valuations, while during cooling periods, project interest and funding quickly decline. This cycle makes the development path of Web3 AI more volatile and narrative-driven. For example, an AI concept lacking substantial progress may still trigger a surge in token prices due to market sentiment; conversely, during a market downturn, even technical advancements may struggle to gain attention.
WE STILL MAINTAIN A "LOW-KEY AND CAUTIOUS EXPECTATION" FOR THE MAIN NARRATIVE OF WEB3 AI, "DECENTRALIZED AI NETWORK", WHAT IF IT HAPPENS? AFTER ALL, THERE ARE STILL EPOCH-MAKING BEINGS LIKE BTC AND ETH IN WEB3. However, at the current stage, we still need to think of some scenarios that can be implemented immediately, such as embedding some AI agents in the current WEB3 project, so as to improve the efficiency of the project itself; Or the combination of AI and some other new technologies can generate new ideas for the crypto industry, even if it is a concept that can attract attention; OR AI PRODUCTS THAT ARE ONLY FOR THE WEB3 INDUSTRY, WHETHER IT IS FROM THE ACCURACY OF THE DATA, OR MORE SUITABLE FOR THE WORKING HABITS OF WEB3 ORGANIZATIONS OR INDIVIDUALS, TO PROVIDE SERVICES THAT PEOPLE IN THE WEB3 INDUSTRY CAN PAY FOR.
To be continued, the next article will mainly review and comment on the five waves of WEB3 AI, as well as some of the products (such as Fetch.AI, TURBO, GOAT, AI16Z, Joinable AI, MyShell, etc.).
