The appetite of AI large models for data is growing bigger and bigger, but traditional cloud server costs are ridiculously high, and data is always worried about being stolen. The Walrus protocol, a distributed storage solution built on the Sui blockchain, directly eliminates these worries.

The core gameplay is actually simple: your files are split into multiple encrypted fragments and stored across thousands of nodes. Even if one-third of the nodes suddenly go offline or are hacked, the remaining nodes can still fully restore the data through erasure coding algorithms. With this design, storage costs are reduced to about one-tenth of centralized cloud services, while maintaining an availability of over 99.99%.

Sui’s parallel execution framework makes the entire system run extremely fast. When developers upload terabyte-scale datasets, 4K videos, or 3D models, there is virtually zero latency. More importantly, the data is encrypted from start to finish, and only those with the keys can access it; node operators cannot peek into the data at all. For AI companies, this means model weights and training data are truly secure.

Imagine these scenarios: in a decentralized AI marketplace, researchers upload datasets, and trainers pay via smart contracts to use them, all with full privacy; or in a metaverse platform, user-generated content is stored permanently on a distributed network, no longer fearing arbitrary deletion by the platform. Developers can integrate the Walrus SDK with just a few lines of code, and node operators can earn $WAL tokens by contributing idle hard drives and bandwidth.

Sensitive data like medical images, business secrets, and personal works can now be securely backed up and never lost. As we enter the AGI era, efficient, private, and censorship-resistant storage needs will become essential, and Walrus has already secured its position within the Sui ecosystem.