From parallel lines to intersections, the deep integration and collision of AI and Web3 has brought more imagination space for innovation in the digital age, and has become an unstoppable development trend. On July 26, the "Future Forward AI+Web3.0 Integration and Reconstruction" event jointly organized by PANews and ZAN, a Web3 brand under Ant Financial, was officially held in Shanghai. The event invited many big names in the fields of AI and Web3 to discuss how AI and Web3 technologies can be integrated to promote fundamental changes in the digital field.
With the continuous optimization of algorithms such as deep learning and reinforcement learning, AI has become an important force in promoting the development of productivity. More and more technologies are combined with it to achieve a strong growth curve. Web3+AI is one of the hot sectors in the market. The combination of the two has unleashed powerful integration and innovation potential in promoting the fission of the application ecosystem and the innovation of industry models.
In his speech titled "AI: The Next Potential Large-Scale Application of Web3", Conflux co-founder Zhang Yuanjie said that blockchain and artificial intelligence have a relatively long-term prospect. 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, judging from the amount of financing related to Web3+AI this year, it only accounts for about 1% of the global AI enterprise financing.
He further pointed out that there are differences between blockchain and artificial intelligence in terms of functions, nature, methods, identity and content processing. For example, the implementation path of blockchain is bottom-up, while artificial intelligence is top-down, but the combination of the two can solve many problems, such as the monopoly of computing network models, data, computing power costs and economic resources; the problems that Web3+AI projects are currently trying to solve are concentrated in the decentralized computing power market, decentralized AI model network, decentralized sub-model training, public data for AGI large model training and reasoning, private data and end models of private AI, AI agents and applications, etc., combined with blockchain networks to attract a large number of users through token incentives, computing power, data and capital participation; of course, there are also many challenges at present. The development of technologies such as AI model training and computing power scheduling and processing in decentralized networks still has great limitations. The data market also lacks effective collation and analysis, pricing and privacy protection. The functions of AI agents and applications are still relatively monotonous and isolated.
However, issues such as high costs, low utilization efficiency, and security and privacy challenges are hindering the realization of large-scale applications, which also places higher demands on infrastructure. Kverson, product manager of ZAN Infra, pointed out that data infrastructure can promote the efficient integration of AI and Web3. ZAN has a variety of business combinations in Web3 and AI. For example, most of the cost of the node services provided by ZAN comes from storage fees, and through its cooperation with Ant LETUS integration independently developed by ZAN can reduce storage costs by 30% and significantly improve storage I/O efficiency; in terms of parallel processing of requests, ZAN can achieve reasonable routing of online and offline processing requests through self-developed algorithms, ensuring accurate Response and real-time efficiency; cloud native can realize dynamic scheduling of nodes, and can maximize the use of resources such as nodes to ensure the performance of processing user requests; the cloud platform provides the most stable and economical server and network resources for ZAN Node.
With the coming of AI and Web3, data sovereignty is returning, system efficiency is improving, security is enhanced, and value exchange is innovating... Web3 and AI combined with narrative present unlimited potential far beyond our imagination, so when will this disruptive moment come? In a fireside chat hosted by Xiao Xigua, the head of user growth at DBunker, with the theme of "Has the AI+Web3.0 singularity arrived?", Mike, the founder of Goplus, said that the integration of AI+Web3 is a trend, but it will go through three major stages. The first is that Web3 improves the efficiency of AI, the second is that AI solves the underlying problems on Web3, and the final stage will be truly integrated. He also believes that the introduction of Web3 can also bring solutions to the moral and ethical issues of AI.
Sanzhi, the head of Pond Asia Pacific, pointed out that there are certain monopoly problems in the current development of the AI field. For example, ChatGPT changed the way of content search through data collection, but it also made content creators lose content ownership and income. The incentive mechanism of Web3 can solve this problem of sharing. In this regard, Gigi, the BD director of Privasea AI, also agreed. She believes that Web3+AI can enable users to maintain control over data and privacy while realizing user data collection. In Web3+AI application scenarios, for example, AI can be used to screen users of user projects, including responding to witch attacks.
"AI can help companies better present user needs, and compared to high-cost large models, small AI models are easier to reduce usage costs while reaching a wider range of users." Kris, the Greater China ambassador of The Sandbox, believes that it is more important to use Web3+AI to better activate ecosystem users and enable more application scenarios. Karin Kong, an AI and technology investment researcher, 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 sustainable and healthy economic development to the AI field.
"AI is composed of three elements: algorithms, computing power, and data. High-quality data is the decisive factor for the birth of high-quality AI. Although the blockchain data processing process is easy to obtain, its utilization is lagging behind due to inefficiency, complexity, and monopoly issues. The market needs a community-driven, efficient, secure, and trusted data infrastructure, in which AI can realize new data interaction methods, and Web3 can make data more efficient and secure." Chainbase Chief Product Officer Lewis pointed out in a speech entitled "Full-chain Data Network in the AI Era".
By redefining the business order and relationships, the combination of Web3+AI is gaining more and more attention and participation in applications due to its transformative potential, and has become a track favored by market funds. So how can we better grasp investment opportunities? In a fireside conversation on "Investment Layout in the Era of Digital Reconstruction" hosted by OKG Research Chief Researcher Hedy, Chen Yuetian, founding partner of Fire Phoenix Capital, believes that the Web3+AI track has a very strong ability to attract money, but the overall application development will not be fast. Ken, head of Web3port Foundation, said that although AI has a very large scale in the investment circle, it is too early to talk about applications. For promising areas, Ken believes that the market needs more participants, such as the payment track, which can bring incremental markets.
"There are many Web3+AI concept projects that have been implemented, such as using AI tools to help Web3 users with investment warnings and decision-making. In terms of investment strategy, observing fund movements and investment timing are crucial." Nemo, investment manager of Web3.com Ventures, pointed out. Dawn Yang, an angel investor at Sharding Capital, also believes that AI can only play a role in helping investors make auxiliary decisions, but cannot become decision-making information. In terms of investment types, he believes that industry funds should pay more attention to application projects. Owen, founder of PAKA Fund, further added that the starting point determines the investment thinking, and the degree of assistance of AI investment depends on the size of the funds.
