From the convergence and collision of AI and Web3, a deeper integration has brought more room for imagination to the innovation of the digital era, and has become an unstoppable trend. On July 26, the "Future Forward AI+Web3.0 Integration and Reconstruction" event jointly organized by PANews and ZAN, the Web3 brand under Ant Group, was officially held in Shanghai. The event invited many big names in the AI and Web3 fields to discuss how the integration of AI and Web3 technologies can promote fundamental changes in the digital domain.

With the continuous optimization of algorithms such as deep learning and reinforcement learning, AI has become an important force driving the development of productivity. More and more technologies are combined with AI to achieve strong growth curves. Web3+AI is one of the hot sectors in the market, and their combination has erupted with powerful potential for fusion and innovation in driving application ecosystem fission and industry model innovation.

Zhang Yuanjie, co-founder of Conflux, stated in his speech on "AI: The Next Potential Large-Scale Application of Web3" that blockchain and artificial intelligence have long-term prospects. Currently, there are at least 360 Web3+AI projects in the industry, covering infrastructure, data, computing and computing power, education, DeFi, and cross-chain. However, from the perspective of Web3+AI related financing this year, it only accounts for about 1% of the global AI enterprise financing.

He further pointed out that blockchain and artificial intelligence have differences in functionality, nature, methods, identity, and content processing. For example, the implementation path of blockchain is from bottom to top, while that of artificial intelligence is from top to bottom. However, the combination of the two can solve many problems, such as the monopoly of computing network models, data, computing costs, and economic resources. Currently, the problems that Web3+AI projects are trying to solve are concentrated in decentralized computing power markets, decentralized AI model networks, decentralized sub-model training, public data for AGI large model training and reasoning, private data for private AI and end models, AI agents, and applications. The combination of blockchain networks attracts a large number of users, computing power, data, and capital through token incentives. However, there are still many challenges, such as the technical development limitations in AI model training and computing power scheduling in decentralized networks, the lack of effective organization, analysis, pricing, and privacy protection in the data market, and the relatively monotonous and isolated functionality of AI agents and applications.

However, high costs, low utilization efficiency, and security and privacy challenges are hindering the realization of large-scale applications, which also pose higher requirements for infrastructure. Kverson, the product manager of ZAN Infra, pointed out that data infrastructure can promote the efficient integration of AI and Web3. ZAN has various business combinations in Web3 and AI. For example, most of the costs in the node services provided by ZAN come from storage fees. By integrating with LETUS independently developed by AntChain, it can reduce storage costs by 30% and significantly improve storage I/O efficiency. In terms of parallel processing, ZAN can achieve reasonable routing of online and offline processing requests through independently developed algorithms, ensuring accurate response and real-time efficiency. Cloud-native technology can achieve dynamic scheduling of nodes, maximizing the use of resources such as nodes to ensure the performance of processing user requests, and the cloud platform provides the most stable and economical servers and network resources for ZAN Node.

With the surge of AI and Web3, the narrative of the combination of data sovereignty, system efficiency improvement, enhanced security, and innovative value exchange presents unlimited potential far beyond our imagination. When will this disruptive moment arrive? In the fireside chat hosted by DBunker's user growth manager, Little Watermelon, with the theme "Has the AI+Web3.0 singularity arrived?", Mike, the founder of Goplus, stated that the integration of AI+Web3 is a trend, but it will go through three stages: first, Web3 will improve the efficiency of AI; second, AI will solve the underlying problems on Web3, and the final stage will truly integrate the two. He also believes that the introduction of Web3 can bring solutions to the ethical issues of AI.

Sanzhi, the head of Pond in the Asia-Pacific region, pointed out that there are certain monopoly issues in the current development of the AI field. For example, ChatGPT has changed the way content search is done through data collection, but it has also caused content creators to lose ownership and income. The incentive mechanism of Web3 can solve this revenue sharing problem. Privasea AI's BD director, Gigi, also agreed, stating that Web3+AI can allow users to maintain control of their data and privacy while collecting user data. In Web3+AI application scenarios, AI can be used for real user project screening, including dealing with Sybil attacks, and more.

"AI can help companies better present user needs, and compared to high-cost large models, AI small models are easier to reduce usage costs while reaching a larger user base." Kris, the Greater China ambassador of The Sandbox, believes that it is more important to better activate the ecological users and empower more application scenarios through Web3+AI. Karin Kong, who specializes in AI and technology investment research, believes that the metaverse is the largest application product of AI, and applications are more likely to appear in the infrastructure field. Web3 can bring sustained and healthy economic development to the AI field.

"AI is composed of algorithms, computing power, and data, among which high-quality data is the decisive factor for the birth of high-quality AI. Although the process of handling blockchain data is easy to obtain, the low efficiency, complexity, and monopoly issues have led to a lag in utilization. The market needs a community-driven, efficient, and secure trusted data infrastructure, where AI can achieve new data interaction methods, and Web3 can make data more efficient and secure." Lewis, the Chief Product Officer of Chainbase, pointed out in his speech on "The Full-Chain Data Network in the AI Era."

By redefining business order and relationships, the combination of Web3+AI is increasingly being valued and participated in for its transformative potential in applications, and has become a favored track for market funds. So, how can we better grasp investment opportunities? In the fireside chat on "Investment Layout in the Era of Digital Reconstruction" hosted by Hedy, the chief researcher of OKG Research, Chen Yuetian, founding partner of Fire Phoenix Capital, believes that the Web3+AI track has a very strong ability to attract funds, but the overall application development will not progress quickly. Ken, the head of Web3port Foundation, stated that although AI has a very large volume in the investment circle, it is still too early to talk about applications. Regarding the promising areas, Ken believes that the market needs more participants, such as the payment track, which can bring incremental markets.

"There are currently many grounded Web3+AI concept projects, such as using AI tools to help Web3 users with investment warnings and decisions. In terms of investment strategy, observing fund trends and investment timing are crucial." Nemo, an investment manager at Web3.com Ventures, pointed out. Dawn Yang, an angel investor at Sharding Capital, also believes that AI can only play a role in assisting investors in decision-making, and cannot be the sole source of information. In terms of investment types, she believes that industry funds should pay more attention to application projects. Owen, the founder of PAKA Fund, further added that the starting point determines the investment mindset, and the degree of AI investment assistance depends on the scale of the funds.

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