Many people now when talking about AI x Web3, their first reaction is tokenizing AI or AI agent trading.

But if the underlying infrastructure doesn't change, these applications will be hard to truly scale.
That's also why I started paying attention to @0G_labs. Because it addresses not the application problem, but a deeper underlying contradiction.
Blockchain networks naturally emphasize consensus and security, while AI systems emphasize throughput and computational efficiency. These two goals are actually conflicting in traditional architectures.
0G's idea is to split different functions through modular design. The data availability network is responsible for high-throughput data publishing, the storage layer handles persistence, and the execution layer manages application logic.
This way, each layer can be independently scaled.
It may look like just a technical structural adjustment, but it has significant implications for the industry. Because it’s the first time AI workloads can run on-chain, rather than being forced onto centralized servers.
If this architecture proves effective, many future AI applications might directly treat blockchain as infrastructure, rather than just a settlement layer.
@Galxe @GalxeQuest @easydotfunX @wallchain @TermMaxFi