If you break down Web3's development over the past few years, you'll notice a very clear structure.

The on-chain world has already become very good at handling value.
Trading, lending, derivatives, liquidity—all financial matters are continuously being optimized. But once the conversation shifts to AI, a new bottleneck suddenly appears.
Where is the data?
How is computing power allocated?
How are models invoked?
Many AI projects solve for the model itself, but few people redesign the underlying infrastructure.
@0G_labs's approach is actually quite straightforward. Rather than building a new AI model, it's constructing an entire on-chain infrastructure stack for AI, including modularized data availability layers and scalable storage networks, allowing AI training data, models, and inference to flow in a more open environment.
The first time I understood this structure, it felt like watching a new operating system being built.
If large-scale on-chain AI really does emerge in the future, there will definitely need to be a new coordination layer between data, computation, and models.
Maybe many people right now still just see AI as an application, but when infrastructure begins to take shape, you'll discover something else.
AI might be slowly becoming the core driving force of the next generation on-chain economy.
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