The upper limit of an AI system's capabilities is often determined by data quality. If the source data is not up to standard, no matter how complex the algorithm, it will be difficult to break through the bottleneck.

Walrus has put a lot of effort into the underlying architecture—ensuring data verifiability, provability, and trustworthiness through on-chain mechanisms. What are the benefits of doing this? It allows AI to not only run fast but also run stably and be used with confidence.

A reliable data infrastructure is becoming the key competitive advantage for the next generation of AI applications.