If we look back at the history of blockchain development, we will find a pattern.

Each cycle introduces new infrastructure layers that push the previous generation of applications to larger scales.
Ethereum made smart contracts possible, Layer 2 solutions addressed scalability issues, and now AI is bringing the on-chain world to a new stage.
@0G_labs likely plays the role of a new data infrastructure at this stage.
The core resource of AI is not computing power, but data.
The problem is that today, almost all data is controlled by large platforms, and the training process is completely unverifiable.
For the Web3 world, this is a huge asymmetry.
0G's attempt is to introduce data availability and computational verification capabilities into AI networks.
The significance of this is not just a technological upgrade, but a shift in the power structure.
Data is no longer owned solely by centralized platforms but can be verified and shared on-chain.
For developers, this means new application models are emerging.
AI models can become on-chain assets, training data can be tracked and incentivized, and computing resources can form a market.
Many people like to see the combination of AI and Web3 as a narrative.
But once the infrastructure is truly established, it will gradually evolve into a new industrial structure.
If in the future, on-chain applications start to feature many AI Agents, data markets, and decentralized training networks, projects like 0G are very likely to become the foundational soil for all of this.
@Galxe @GalxeQuest @easydotfunX @wallchain @TermMaxFi