We are now facing a rather ironic situation. Humanity has developed telescopes capable of observing galaxies, detectors that can capture particle collisions, and devices that can scan brainwaves... but all the data collected by these sophisticated instruments ultimately become isolated islands. Weather satellite data and social media sentiment are completely out of sync, power grid sensors can't interpret pandemic curves, and various digital sensors are like severed nerve endings, each acting independently.

Why is this happening? Essentially, we have been using a centralized approach—dumpting all data into a single repository and waiting for humans to sift through and analyze it. It's like each muscle in the body sending signals separately to different brain regions, never able to coordinate in real-time. The result? No matter how much data there is, it remains dead data.

The Walrus Protocol, combined with Sui to form the "programmable data object" model, seems to be trying a different path. It doesn't aim to build a one-size-fits-all brain, but instead designs a protocol that allows each data source—whether it's a street corner sensor or a space telescope—to package its data stream into "neural cells" with autonomous behavior and a unified interface. These cells interact and self-organize within a decentralized network, ultimately emerging with holistic perception and predictive capabilities. This is what data infrastructure should look like.