Recently, more and more developers are discussing a question: if AI truly is the core application of the next-generation internet, can existing blockchain architectures really support this scale of data and computation?

Most blockchains are actually designed for financial transactions. Transactions are discrete events, with limited data volume, and verification logic is relatively simple. But AI is completely different. Model training, inference, data updates—these processes are essentially continuous data streams.
The first time I seriously studied @0G_labs's architecture, I realized a very critical point. It’s not just about simply improving performance, but about redefining how the chain should handle data from the ground up.
By modularizing the structure to separate data availability, storage, and execution layers, the network can be specifically optimized for AI data streams. This design allows the chain to no longer just record transactions but to support real data workloads.
This has a profound impact on the industry. In the past, Web3 mainly addressed value flow issues, but in the AI era, what is truly scarce are data and computing power. If the chain can become part of a data network, the entire ecosystem’s application structure will change.
From a user experience perspective, this change won’t be very obvious in the short term. But once AI Agents and decentralized model markets start to emerge, people will gradually realize that many underlying applications have already switched to a new infrastructure.
@Galxe @GalxeQuest @easydotfunX @wallchain @TermMaxFi