After the Meme frenzy, is it a mess or a rebirth?

Introduction

Since the emergence of ChatGPT at the end of 2022, the AI sector has become highly sought after in the cryptocurrency field. The nomads of WEB3 have already embraced the idea that "any concept can be hyped," not to mention the unlimited narrative threads and application capabilities of AI in the future. Therefore, in the crypto circle, the AI concept initially gained popularity as a "Meme craze" for a while, and then some projects began exploring its actual application value: what new practical applications can cryptocurrency bring to the rapidly advancing AI?

This research article will describe and analyze the evolution path of AI in the Web3 field, from the early hype wave to the current rise of application projects, and will use cases and data to help readers grasp the industry context and future trends. Let's throw out an immature conclusion right at the beginning:

• 01, The era of AI memes is already a thing of the past; what has been cut and what has been earned should remain as eternal fragments of memory.
• 2. Some basic WEB3 AI projects have consistently emphasized the benefits of "decentralization" for AI security, but users are not very convinced; what users care about is whether the "tokens are profitable" and whether the "product is easy to use".
• 3. If you want to ambush AI-related cryptocurrency projects, the focus should shift to pure application-type AI projects or platform-type AI projects (which can concentrate many tools or agents that are easy for end-users to use). This may be a longer-term wealth hotspot after AI Memes.

The development path differences of AI in Web2 and Web3

AI in the Web2 World

In the Web2 world, AI is primarily 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, with algorithms and data not disclosed, leaving users to only use their results, which lack transparency. This centralized control results in AI decisions being unaccountable, leading to issues of bias and unclear responsibility. 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 pain point of opacity has led to the rise of new AI projects in 2025 like Deepseek, which seem open-source but are actually "fishing in a barrel."

In addition to the opaque flaws, large AI models in WEB2 also face two other pain points: insufficient user experience across different product forms and inadequate accuracy in specialized niche markets.

For example, if users want to create a PPT, an image, or a video, they will look for new AI products with lower entry barriers and better user experiences to use, and they are willing to pay for them. Currently, many AI projects are attempting to create no-code AI products to lower the entry barriers for users even further.

For many users of WEB3, they have likely experienced the feeling of powerlessness when using ChatGPT or DeepSeek to obtain information about a specific crypto project or token. The data from large models cannot yet accurately 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 precise data and analysis within 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.

Leveraging the decentralized architecture of blockchain, Web3 AI projects often claim to emphasize open-source code, community governance, and transparency, aiming to disrupt the traditional AI monopoly held by a few companies in a distributed manner. For example, some projects explore using blockchain to verify AI decisions (zero-knowledge proofs ensure model output is trustworthy) or having DAOs review AI models to reduce bias.

Ideally, Web3 AI pursues "open AI", so that model parameters and decision-making logic can be audited by the community, and at the same time, developers and users are incentivized to participate through the token mechanism. However, in practice, the AI development of Web3 is still limited by technology and resources: it is extremely difficult to build decentralized AI infrastructure (training large models requires massive computing data, but no WEB3 project can reach a fraction of OpenAI's amount of funds), and a small number of projects that claim to be Web3 AI still rely on centralized models or services, but only integrate some blockchain elements into the application layer. At least the application is still being developed in real life; However, the vast majority of WEB3 AI projects are still pure memes, or memes under the banner of real AI.

Moreover, 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, resulting in a relatively stable cycle. In contrast, Web3 AI combines the speculative attributes of the cryptocurrency market, often experiencing "waves" of enthusiasm that fluctuate dramatically with market sentiment: when a concept is hot, funds flood in, driving up token prices and valuations; when it cools down, the project's popularity 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 might see its token price soar due to market sentiment; conversely, during a downturn, even technical advancements struggle to attract 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 following article will mainly review and comment on the five waves of the WEB3 AI boom, as well as some of the products (such as Fetch.AI, TURBO, GOAT, AI16Z, Joinable AI, MyShell, etc.).

Reference Article:

[ Web3 AI vs. Web2 AI: Why Open-Source and Transparency Will Win ](