How to quickly master the market hotspots, technical trends, ecological progress, and governance situation happening in the Web3 industry? The "Market Trend Observation" column launched by Web3Caff Research will delve into the current hot events and provide value interpretation, comments and principle analysis. Look at the essence through the phenomenon, and immediately follow us to quickly capture the latest market trends in Web3.
Author: wuyue.eth, Web3Caff Research Researcher
Cover: Logo by this project, Typography by Web3Caff Research
Word Count: The full text is over 2100+ words
Currently, the AI and Blockchain fields are accelerating their development, but facing some key issues that hinder their deep integration and widespread application. First, at the data level, the intelligent decision-making and training of AI highly depend on high-quality, scalable data. However, the existing technologies are not efficient enough in the storage and processing of on-chain and off-chain data, and cannot meet the high-frequency and diversified data demands of AI agents. In addition, the transparency and verifiability of off-chain data storage are relatively poor, which makes the AI reasoning process lack a foundation of trust. Furthermore, at the execution level, although the existing AI agent frameworks (such as ELIZA, ARC and Swarms) have optimized the performance of single AI agents, they are obviously insufficient in terms of reasoning verification, transparency and operational traceability, lacking a trustworthy execution environment. In addition, traditional Blockchain platforms are often just accounting tools, unable to provide decentralized mechanisms to ensure the fairness and immutability of AI agents. At the same time, the efficiency of AI agents in multi-agent collaboration and knowledge sharing is relatively low, and the current technical framework is difficult to support the seamless interoperability and collaborative work between AI agents. In terms of computing power, the demand of AI agents for complex computing tasks is constantly increasing, but the computing power and scalability of the existing Blockchain platforms are difficult to meet the needs of running AI models, becoming a performance bottleneck.
