Overview
This article discusses how Subsquid enables AI development through blockchain data access. The main argument is that quality data forms the foundation for effective AI systems.
Data as AI’s Foundation
AI is only as intelligent as the data it’s been given. Without high-quality training datasets, AI models produce poor outputs, including hallucinations and biased results. GPT-3, for example, required 570 GB of text data for training.
Blockchain Data Advantages
Subsquid positions itself as solving a critical problem: while blockchain data is theoretically public, extracting it directly from nodes remains difficult. The platform offers decentralized access to data from over 150 EVM, SVM, and Substrate networks through its data lake and query engine.
Practical Applications
Specific use cases include:
- Developing trading bots that perform well during market downturns
- Training AI models to recognize security threats in blockchain systems
- Creating models for MEV (Maximal Extractable Value) research
Core Value Proposition
Subsquid’s appeal lies in providing high-quality, curated data in accessible formats for AI researchers and developers, while maintaining the integrity advantages of decentralized systems.
Data can exist without AI, but AI cannot function without data.