1. Weak Correlation Between AI and Web3 Data and Investment Behavior

Although AI has achieved tremendous success in traditional finance, its application in the Web3 crypto market still faces significant challenges. The core characteristics of the Web3 ecosystem are decentralization and openness, with data primarily distributed across on-chain and off-chain segments. The fragmentation between on-chain data (such as transaction records and smart contract interactions) and off-chain data (such as market sentiment and news events) severely hinders AI's comprehensive analytical capabilities.

Traditional AI excels at processing centralized datasets, generating precise predictive models through large-scale training. However, the decentralized nature of data in Web3 complicates data collection and integration. Moreover, investment behavior in the Web3 market is often driven by irrational factors, such as emotional fluctuations, public opinion, and community consensus, which are challenging for traditional AI to model effectively. This weak correlation limits the predictive accuracy of AI in investment decisions, making it difficult for investors to rely on intelligent tools for generating returns.

Breakthrough Direction：Omnipilot is committed to addressing this weak correlation issue by establishing an efficient framework for integrating on-chain and off-chain data analysis through a multi-agent collaborative network and large model technology. Based on this, AI can not only track the movements of "smart money" but also capture market sentiment in real time, providing users with more precise and comprehensive investment recommendations.