Many people look down on Walrus, and the fundamental reason is that they are still viewing new problems through old thinking. In the past few years' cycles, metrics like liquidity, computing power, and TPS took all the spotlight, while data storage was merely treated as an ancillary issue to be casually addressed. But now, things are different—on-chain applications are exploding, AI models are emerging one after another, decentralized content platforms are rising, and the demand for long-term data validation is surging. Data itself has suddenly become the core of systemic contradictions. This is exactly what a certain data storage protocol has been emphasizing.

It is not competing for profit rankings with anyone; its true opponent is an inevitable challenge: how to keep data alive long-term? How to prove it has not been tampered with? How to reuse it repeatedly without depreciation? When data volume explodes and access frequency rises, the problems of centralized storage will be magnified infinitely, yet on-chain systems cannot hold all raw data. This contradiction is itself nurturing new infrastructure needs.

What makes this protocol powerful is—it's not claiming to be a revolutionary disruptor. Instead, it breaks down data issues into very detailed parts, solving them at the protocol level through mechanisms rather than concepts. So you might feel its narrative progress is slow, but its logical chain is rock-solid. It doesn't need to generate hot topics every day; genuine demand will naturally emerge as the system is used by more and more people.

When more developers regard data security, usability, and long-term proof of existence as basic prerequisites, such solutions will upgrade from "optional tools" to "infrastructure." Only then will the market realize that its value does not come from emotional fluctuations but from the degree of reliance.