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Looking at Walrus's storage solution, it is indeed a bit different. Most distributed storage projects play the "multiple copies" approach, but Walrus takes a different route—using erasure coding to split data into fragments and distribute them across different nodes.
The clever part is that as long as you collect enough fragments, you can reconstruct the complete data. If a node goes offline? No problem. This approach directly reduces storage redundancy costs from dozens or even hundreds of times down to around 4.5 times. It sounds abstract, but from another perspective—this is using mathematics and engineering to solve real economic problems.
Instead of flashy concepts, it focuses on optimizing efficiency in real-world scenarios. This kind of thinking is actually quite rare in Web3 infrastructure.