Modularization is rewriting the infrastructure, with @0G_labs paving a longer path.

Traditional blockchain designs tend to bundle all functions together, but this approach begins to struggle when facing AI demands, as AI requires much higher data and performance standards than conventional applications.
@0G_labs has chosen a more complex but more rational path, splitting the system into multiple modules, each focusing on solving a specific problem. Data availability, storage, and execution can be scaled separately, giving the overall system greater resilience.
This modular approach is actually very similar to modern AI architecture. Models, data, and computing power are inherently separate; it just requires an efficient way to connect them. The significance of @0G is that it provides the foundation for this connection.
From a developer’s perspective, this means lower development costs and greater flexibility. Applications can call different modules as needed, rather than being limited by a single architecture.
In the long run, infrastructure competition will not only focus on performance but also on the rationality of the structure. What @0G is doing is making the system closer to real needs, rather than optimizing around existing paradigms.
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