Exploring AI and Web3: Industry Leaders Discuss Future Opportunities and Challenges
On July 26, the "Future Forward AI+Web3.0 Fusion and Reconstruction" event, jointly organized by the leading Chinese blockchain media PANews and Ant Digital's Web3 brand ZAN. The event invited numerous prominent figures in the fields of AI and Web3 to explore how these technologies can be integrated to drive fundamental changes in the digital sector.
From parallel lines to intersections, the deep integration and collision of AI and Web3 have opened new avenues for innovation in the digital age, becoming an unstoppable development trend. On July 26, the "Future Forward AI+Web3.0 Fusion and Reconstruction" event jointly organized by PANews and Ant Digital's Web3 brand ZAN was officially held in Shanghai. The event invited many experts to discuss the potential of AI and Web3 technologies in transforming the digital landscape.
With continuous advancements in algorithms such as deep learning and reinforcement learning, AI has become a significant force in driving 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 exploded with strong potential for integration and innovation in promoting the fission of the application ecosystem and the innovation of industry models.
In his speech entitled "AI: The Next Potential Large-Scale Application of Web3", Conflux Co-Founder Zhang Yuanjie highlighted the long-term prospects of blockchain and AI. He noted that there are over 360 Web3+AI projects covering various sectors, including infrastructure, data, computing, education, DeFi, and cross-chain. However, Web3+AI-related financing only accounts for about 1% of global AI enterprise funding.
Zhang further pointed out the differences between blockchain and AI 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. He discussed how their combination can address issues like monopolies in computing models, data, and economic resources, despite current challenges such as high costs and limited development in decentralized networks.
At present, the problems that Web3+AI projects try 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, computing power, data and capital participation through token incentives; of course, there are also many challenges at present. The development of technologies such as AI model training and computing power scheduling in decentralized networks is still very limited. 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, problems such as high costs, low utilization efficiency and security and privacy challenges are hindering the realization of large-scale applications, which also puts higher requirements on infrastructure.
Kverson, Product Manager of ZAN Infra, emphasized that data infrastructure can promote the efficient integration of AI and Web3. ZAN has a variety of business combinations in Web3 and AI, significantly reducing storage costs and enhancing efficiency through their proprietary technologies. For example, most of the cost of the node services provided by ZAN comes from storage fees. By integrating with LETUS independently developed by Ant Chain, it 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 nodes and other resources to ensure the performance of processing user requests. The cloud platform provides the most stable and economical server and network resources for ZAN Node.
During a fireside chat on "Is the AI+Web3.0 Singularity Coming?" - hosted by Xiao Xigua, Head of User Growth of DBunker , Mike, Founder of Goplus, outlined the three stages of AI and Web3 integration: improving AI efficiency, solving underlying Web3 problems, and achieving true integration. He also discussed how Web3 could address AI's moral and ethical issues.
Sanzhi, 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 content is searched through data collection, but it also made content creators lose content ownership and income, and the incentive mechanism of Web3 can solve this problem of sharing. In this regard, Gigi, BD Director of Privasea AI, also agreed. She believes that Web3+AI can allow users to maintain control and privacy over data 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.
By redefining the business order and relationships, the combination of Web3+AI is increasingly valued and participated in the application of its transformative potential, and has become a track favored by market funds. So how can we better grasp investment opportunities? In the fireside dialogue on "Investment Layout in the Era of Digital Reconstruction" hosted by Hedy, 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 money, but the overall application development will not be fast. Ken, Head of Web3port Foundation, said that although AI has a very large volume in the investment circle, it is too early to talk about applications. For optimistic areas, he believes that the market needs more participants, such as the payment track can bring incremental markets.
SOURCE PANews
From parallel lines to intersections, the deep integration and collision of AI and Web3 have opened new avenues for innovation in the digital age, becoming an unstoppable development trend. On July 26, the "Future Forward AI+Web3.0 Fusion and Reconstruction" event jointly organized by PANews and Ant Digital's Web3 brand ZAN was officially held in Shanghai. The event invited many experts to discuss the potential of AI and Web3 technologies in transforming the digital landscape.
With continuous advancements in algorithms such as deep learning and reinforcement learning, AI has become a significant force in driving 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 exploded with strong potential for integration and innovation in promoting the fission of the application ecosystem and the innovation of industry models.
Keynote Speeches and Insights
In his speech entitled "AI: The Next Potential Large-Scale Application of Web3", Conflux Co-Founder Zhang Yuanjie highlighted the long-term prospects of blockchain and AI. He noted that there are over 360 Web3+AI projects covering various sectors, including infrastructure, data, computing, education, DeFi, and cross-chain. However, Web3+AI-related financing only accounts for about 1% of global AI enterprise funding.
Zhang further pointed out the differences between blockchain and AI 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. He discussed how their combination can address issues like monopolies in computing models, data, and economic resources, despite current challenges such as high costs and limited development in decentralized networks.
At present, the problems that Web3+AI projects try 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, computing power, data and capital participation through token incentives; of course, there are also many challenges at present. The development of technologies such as AI model training and computing power scheduling in decentralized networks is still very limited. 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, problems such as high costs, low utilization efficiency and security and privacy challenges are hindering the realization of large-scale applications, which also puts higher requirements on infrastructure.
The Role of Data Infrastructure
Kverson, Product Manager of ZAN Infra, emphasized that data infrastructure can promote the efficient integration of AI and Web3. ZAN has a variety of business combinations in Web3 and AI, significantly reducing storage costs and enhancing efficiency through their proprietary technologies. For example, most of the cost of the node services provided by ZAN comes from storage fees. By integrating with LETUS independently developed by Ant Chain, it 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 nodes and other resources to ensure the performance of processing user requests. The cloud platform provides the most stable and economical server and network resources for ZAN Node.
Panel Discussions: The Singularity of AI and Web3
During a fireside chat on "Is the AI+Web3.0 Singularity Coming?" - hosted by Xiao Xigua, Head of User Growth of DBunker , Mike, Founder of Goplus, outlined the three stages of AI and Web3 integration: improving AI efficiency, solving underlying Web3 problems, and achieving true integration. He also discussed how Web3 could address AI's moral and ethical issues.
Sanzhi, 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 content is searched through data collection, but it also made content creators lose content ownership and income, and the incentive mechanism of Web3 can solve this problem of sharing. In this regard, Gigi, BD Director of Privasea AI, also agreed. She believes that Web3+AI can allow users to maintain control and privacy over data 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 is composed of three elements: algorithms, computing power and data. Among them, high-quality data is the decisive factor for the birth of high-quality AI. Although the processing process of blockchain data is easy to obtain, it is also backward in utilization due to inefficiency, complexity and monopoly. The market needs a community-driven, efficient and secure 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".
Investment Opportunities in Web3+AI
By redefining the business order and relationships, the combination of Web3+AI is increasingly valued and participated in the application of its transformative potential, and has become a track favored by market funds. So how can we better grasp investment opportunities? In the fireside dialogue on "Investment Layout in the Era of Digital Reconstruction" hosted by Hedy, 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 money, but the overall application development will not be fast. Ken, Head of Web3port Foundation, said that although AI has a very large volume in the investment circle, it is too early to talk about applications. For optimistic areas, he believes that the market needs more participants, such as the payment track can bring incremental markets.
"There are also many Web3+AI concept projects that have been implemented, such as using AI tools to help Web3 users make investment warnings and decisions. In terms of investment strategy, observation of capital trends and investment timing are crucial." Nemo, Investment manager of Web3.com Ventures, emphasized. Dawn Yang, an angel investor at Sharding Capital, also pointed out that AI can assist in making investment decisions but should not be the sole basis. He believes that industry funds should pay more attention to application projects. Owen, Founder of PAKA Fund, added that the starting point determines investment thinking, and the degree of AI's assistance depends on the size of the funds.
SOURCE PANews
No comments: