Is there still a chance for the narrative of Web3+AI in the absence of a bull run?

Introduction

In recent years, with the rapid development of blockchain technology and artificial intelligence, the combination of Web3 and AI has become one of the most关注的 topics in the technology sector. However, this emerging field still faces numerous challenges, including the complexity of technological integration, governance issues of data hegemony, and the contradiction between market speculation and value realization.

At the space hosted by Golden Finance, two industry professionals: Una Wang, Founder and CEO of LingoAI, and LOYAL Luyao engaged in an in-depth discussion on "Is there still an opportunity for Web3 plus AI narrative?" They analyzed the current situation and future directions from multiple dimensions such as technology, ecology, and user trust. The following is a整理与分析 of the core viewpoints of the guests:

1. The Core Proposition of the Integration of Web3 and AI: Data Hegemony and Technological Value

1. The essence of Web3 is to solve the data ownership issue.

Guest Una pointed out that the concept of Web3 was proposed by Tim Berners-Lee, the father of the World Wide Web, over 20 years ago. Its core goal is to break the data monopoly of the Web2 era, allowing users to truly own and control their own data. "In the Web2 model, platforms like Facebook and TikTok monetize user data but do not share the profits with data contributors. Web3, through decentralized protocols, returns data ownership to users and achieves transparent governance through blockchain technology." She emphasized that this transformation can not only address compliance issues such as GDPR but also provide high-quality data sources for AI.

Using ChatGPT as an example, Una illustrates that the training of current AI models is highly dependent on data collection from centralized platforms, but this data often involves privacy abuse and compliance risks. "If users can independently authorize the use of data through Web3 protocols and reap benefits from it, this will provide a compliant and sustainable data ecosystem for AI development." She believes that the natural fit between blockchain and AI lies in the fact that the former solves the problem of data ownership and circulation, and the latter requires massive data to improve model capabilities, and the combination of the two will unleash huge potential.

2. Industry deviates from the main line: excessive pursuit of financial speculation

Several guests mentioned that there is a serious phenomenon of "narrative deviation" in the current Web3 field. Teacher Lu Yao bluntly stated: "Many people equate Web3 with cryptocurrencies and speculative trading, ignoring its technological essence. The chaos in the industry after 2017 has led to the bad money driving out the good, with many project parties only focusing on issuing tokens for cashing out, rather than solving real problems." This shortsighted behavior not only damages the industry's credibility but also leads to a lack of truly phenomenal Web3 applications.

Una further analyzes that the market's misunderstanding of Web3 stems from being "too close to money." "Blockchain and cryptocurrencies inherently possess financial attributes, but if they are only viewed as speculative tools, the industry will fall into a deadlock. The real value should be reflected in addressing core pain points such as solving data monopolies and enhancing user experience through technology."

2. Challenges and Breakthrough Paths of Technological Integration

1. The contradiction between privacy protection and transparency

When discussing the technical challenges of the integration of Web3 and AI, privacy protection becomes the focus. The host asked, "The transparency of blockchain conflicts with the data privacy required for AI training; will this become a stumbling block for integration?" Una responded that this contradiction can be resolved through a layered authorization mechanism. "Users can autonomously choose to open non-sensitive data for AI model training, while the privacy-related parts are protected through encryption technology. For example, zero-knowledge proof-based protocols can verify data validity without exposing the original data."

Lu Yao added that transparency itself is the foundation of trust. "By recording the entire process of data contribution and usage on the blockchain, it can both prevent data abuse and incentivize user participation. For example, project parties can encourage users to contribute high-quality data through a token reward mechanism, and constrain malicious behavior through an on-chain reputation system."

2. The Gap Between Technical Feasibility and Scenario Implementation

Although the technical solution has taken shape, practical implementation still faces bottlenecks. Una pointed out: "Currently, most projects combining Web3 and AI remain at the conceptual stage, lacking clear business models and essential user needs. Many developers awkwardly embed AI functions into blockchain applications to ride the trend, which instead seems out of place." She believes that the key to success lies in identifying the right scenarios, such as decentralized sharing of medical data and copyright affirmation for creators' content.

Lu Yao took market-making products as an example to propose the application potential of AI in the financial field. "Traditional market makers rely on manual strategies, which carry the risk of market manipulation. If liquidity is automatically provided through AI algorithms, combined with the transparency of blockchain, it can greatly enhance trading fairness." However, he also admitted that such products need to undergo long-term validation to gain user trust. "Capital security, algorithm stability, and compliance are all thresholds that must be crossed."

3. User Trust and Ecosystem Development

1. How to break the stigma that "Web3 is a scam"

Lu Yao, drawing from his own experiences, pointed out that the Web3 industry is facing a serious trust crisis. "When I mention that I work in Web3 in traditional industries, people often associate it with scams or speculation. This stigmatization stems from the chaotic development of early projects and the lack of regulation." He calls on industry participants to focus more on product value rather than short-term hype. "Only by creating applications that truly address users' pain points can we change external perceptions."

Una believes that education and outreach are key. "Many users and even practitioners do not understand the core mission of Web3. We need to enhance public awareness through international cooperation (such as collaborating with the United Nations Internet Governance Forum) while promoting standardized protocols and governance frameworks to reduce industry chaos."

2. Hybrid AI and User Data Sovereignty

In response to the current situation of user data being misused in AI applications, Una proposed a "hybrid AI" solution. "Users can store private data locally or on a decentralized network, granting access only to specific AI agents. For example, personal health data is processed by local AI, while public data (such as weather information) can be accessed using open models like ChatGPT." This model not only protects privacy but also fully utilizes AI capabilities.

She further mentioned that the open-source ecosystem will drive this process. "Open-source models like Meta's Llama and DeepSeek have lowered the technical barriers, enabling more developers to participate in building user-centric AI applications. In the future, every user may have a personal AI assistant, trained on personal data, but data sovereignty will always remain in the hands of the user."

IV. Future Outlook: Technological Accumulation and Ecological Coordination

1. From Speculation to Value: The Survival Rule of Project Teams

For Web3 projects to survive in the long term, they must balance token economics with technical value. "Tokens should not merely be a financing tool, but should be deeply integrated with product functionality. For example, incentivizing users to contribute data, participate in governance, or redeem services through tokens." He suggests that investors focus on the team's background and technical implementation capabilities, rather than blindly chasing market trends.

Una indicates that "the success of ChatGPT is the result of decades of technological accumulation, and Web3 also requires patience. Project teams should focus on niche scenarios, such as enabling cross-platform data flow through blockchain or utilizing AI to optimize the execution efficiency of smart contracts."

2. The Balance Between Regulation and Innovation

The guests unanimously agreed that compliance is an unavoidable topic in the integration of Web3 and AI. Una took Singapore as an example, pointing out that the government needs to enhance investor protection while encouraging innovation. "The FTX incident exposed the vulnerabilities of centralized exchanges; the future combination of decentralized finance (DeFi) and AI could become a breakthrough, but a transparent auditing mechanism and risk isolation framework need to be established."

Lu Yao added that regulation should not be a one-size-fits-all approach. "For example, automated market maker algorithms can achieve real-time monitoring through on-chain records, ensuring fairness while providing data support for regulation. The key is to find a balance between technological innovation and risk control."

Conclusion: Hone Your Skills in a Bear Market, Await the Bloom in a Bull Market

Whether it is the data sovereignty revolution proposed by Teacher Una or the AI market maker product envisioned by Lu Yao, both need to undergo technological iteration and ecological cultivation. The integration of Web3 and AI is not a patchwork, but an inevitable evolution of technology. When data hegemony is broken and user sovereignty is established, we will welcome a fairer and smarter digital era. The realization of this vision requires the commitment and exploration of every participant.

Live replay link:

Part1:

Part2:

Note: This article is based on the live discussion of the guests and does not constitute investment advice. The market has risks, and decisions should be made with caution.