Why do on-chain applications remain focused on finance and haven't truly entered the data-intensive field?

The reason is simple: existing infrastructure can't support it. High-frequency data, large-capacity storage, and low-cost access are all essential, and currently, few systems can meet all these conditions simultaneously.
@0G_labs is precisely aiming to fill this gap. It makes data availability, storage, and computing power modular, attempting to provide foundational support for AI and other applications with high data demands.
This approach is similar to traditional DA, but with a clearer goal: serving AI scenarios.
The key here isn't just technical terminology but the boundary of capability. If on-chain systems can handle more complex data structures, application forms will also evolve accordingly.
Of course, we're still far from maturity. Performance, cost, and developer adoption all need time for validation.
But from the perspective of infrastructure evolution, breakthroughs in the data layer often determine the ceiling of upper-layer applications. @0G is at least trying to push this limit.
@Galxe @GalxeQuest @easydotfunX @wallchain #Ad #Affiliate @TermMaxFi