AI + Blockchain: Chainbase's Layout in Training Data

Amid the convergence of AI and blockchain, Chainbase has become core infrastructure for training data by building a full-chain data network and proprietary AI models. This layout is primarily reflected in the following three aspects:

1. Full-chain Data Integration and Standardization

Chainbase supports real-time data synchronization (with a refresh interval of <span seconds) across 220+ blockchains. Through a four-layer architecture (data access layer, consensus layer, execution layer, and co-processing layer), it transforms fragmented on-chain data into standardized, AI-ready formats. For example, developers can use SQL or natural language query interfaces to extract raw, decoded, and abstracted data, providing high-quality input for AI training.

2. A Vertical Breakthrough in the Proprietary AI Model, Theia

Chainbase has trained Theia, a large-scale crypto-specific model, based on massive on-chain data. Its 7 billion parameters include 200 million crypto-specific parameters, supporting natural language interaction and multimodal analysis. Theia surpasses mainstream models in perplexity (1.184) and BERT score (0.861) and has been applied in scenarios such as real-time data analysis and DeFi risk assessment.

3. Community Building and Economic Incentives

Through a token economy model ($C tokens) and the "Manuscripts" scripting system, Chainbase incentivizes developers to contribute data processing logic, forming a decentralized data collaboration network. Currently, 15,000 developers and over 8,000 projects have joined, processing over 600 million data calls daily, building the data ecosystem foundation for the AGI era.

Summary: Chainbase, with its "data + AI + blockchain" triangular closed loop, solves the issues of accessibility, real-time, and trustworthiness of training data, becoming a key hub for the convergence of Web3 and AI. @Chainbase Official #chainbase