On this extremely crowded day in L1, I have been thinking: when AI demand explodes, can the existing infrastructure support it? After studying the white paper of @Vanar , I stripped away the marketing noise and found that its logic lies not in competing for TPS, but in the 'specialized design' for AI load.
1. From Hash to Semantics: The Ambition of the Neutron Layer
Traditional EVMs only store hashes, while Vanar's Neutron layer attempts to transform unstructured data such as PDFs and contracts into 'smart objects'. This means that in RWA scenarios, compliance documents are no longer external links but part of the on-chain logic.
2. Kayon Layer: The Closed Loop of AI Reasoning
Not only returning AI results back to the chain, but also attempting to solve contextual reasoning within the architecture. Collaborating with Neutron's semantic data, it achieves the complete path of 'data input -> AI processing -> automatic settlement'.
3. Fixed Rate Model: The Killer App for Commercialization
Unlike Ethereum's bidding model, Vanar locks in a single cost. For developers, the predictability of costs is far more important than 'simply low prices'; this is a prerequisite for the large-scale implementation of PayFi applications.
Summary: Although how EVM-compatible chains establish long-term moats remains to be seen, Vanar is building a closed-loop system of computation + storage + reasoning. In the AI + L1 track, this is a sample with great disassembly value.
