Recently, there has been a hot discussion around the "Verifiable AI Economy" concept of a leading public chain. Many people are jumping on related tokens, but few truly understand the narrative behind it.

Imagine if you wanted to deploy AI applications on-chain, what core issues would you face? Data storage. The training data, inference outputs, and verification records are all in the GB to TB range. The mainnet costs of public chains are too high, making long-term storage of such large amounts of data impractical. So what is the solution? It must be a dedicated storage layer.

This is why some compare Walrus to "land," and AI applications to "buildings." One must be established for the other to have meaning.

Looking at the current market price, Walrus is around $0.15. An interesting phenomenon observed on-chain is that for several consecutive days, several large addresses have been repeatedly accumulating within the 0.148 to 0.152 range. This continuous small-scale accumulation usually indicates that someone is building up their position while suppressing the price to trigger retail investors to sell.

When more people realize the core role of storage infrastructure in the AI ecosystem, the valuation logic will reverse. It will shift from "this is a small token" to "this is an essential foundational layer." Historical experience shows that such cognitive shifts are often accompanied by significant price increases.

The current silent period is usually the best opportunity window for early participants.