AI in Crypto: After the Meme Frenzy, is it a Mess or a Rebirth?

The era of AI memes is already a thing of the past; those who should be played people for suckers and those who should earn have been left as eternal memory fragments.

Written by: W Labs GuoTian Laboratory

Introduction

Since ChatGPT made its debut at the end of 2022, the AI sector has been a hot topic in the cryptocurrency space. The nomads of WEB3 have already embraced the idea that "any concept can be hyped up," not to mention AI, which has unlimited narrative contexts and application capabilities in the future. Therefore, within the crypto circle, the AI concept initially surged to 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 evolution path of AI in the Web3 field, from the early hype wave to the current surge of application-based projects, and combine cases and data to help readers grasp the industry context and future trends. Let's throw out an immature conclusion right from the start:

1. The era of AI memes is already in the past; those who should be played people for suckers and those who should earn have left behind eternal fragments of memories.
2. Some basic WEB3 AI projects have always emphasized that "decentralization" can bring benefits to the security of AI, but users are not very convinced. What users care about is whether "tokens can make money" + "whether the product is easy to use";
3. 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 user-friendly tools or agents for C-end users). This might be a longer-term wealth hotspot after the AI Meme.

1. The Development Path Differences of AI in Web2 and Web3

• 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, with algorithms and data that are not made public, leaving users only to utilize their results, which lacks transparency. This centralized control leads to AI decisions being un-auditable, with issues of bias and unclear accountability. Overall, AI innovation in Web2 focuses on enhancing 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 emergence of new AI projects like Deepseek in 2025, which seem open source but are actually "play people for suckers."

In addition to the opaque flaws, large AI models of WEB2 also have two other pain points: insufficient user experience across different product forms and inadequate accuracy in specialized sub-tracks.

For example, if you want to create a PPT, an image, or a video, users will still look for new AI products that have 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 develop no-code AI products to lower the entry barrier for users even further.

For many users of WEB3, there should be a sense of helplessness when using ChatGPT or DeepSeek to obtain information about a specific cryptocurrency project or token. The large model data still cannot 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 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 communities. 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 validate AI decisions (zero-knowledge proofs ensure the trustworthiness of model outputs) or having DAOs review AI models to reduce bias.

In an ideal state, 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 can match even a fraction of OpenAI's). A few projects claiming to be Web3 AI still rely on centralized models or services, only integrating some blockchain elements at the application level. Among these WEB3 AI projects, a few are relatively reliable and have genuine development applications; however, the vast majority of WEB3 AI projects are purely memes or are 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, resulting in a relatively smooth cycle. In contrast, Web3 AI combines the speculative nature of the cryptocurrency market, often experiencing "booms" in cycles that fluctuate dramatically with market sentiments: when a concept is hot, funds flood in, driving up token prices and valuations; when it cools, project 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 may trigger a surge in token prices due to market sentiment; conversely, during a downturn, even technical advancements struggle to gain attention.

We maintain a "low-key and cautious expectation" for the main narrative of WEB3 AI, "decentralized AI networks"; what if it actually becomes a reality? After all, there are monumental existences like BTC and ETH in WEB3. However, at this current stage, everyone still needs to pragmatically conceptualize some immediately applicable scenarios, such as embedding AI Agents into current WEB3 projects to enhance the efficiency of the projects themselves; or combining AI with other new technologies to generate new ideas suitable for the crypto industry, even if they are just concepts that can attract attention; or creating AI products that serve the WEB3 industry, regardless of the accuracy of data or how well they align with the working habits of WEB3 organizations or individuals, to provide services that the crowd in the WEB3 industry can pay for.