On-chain AI infrastructure—are we solving problems or creating a new complex system?

Many projects put data, computation, and storage all on the chain, which seems comprehensive but also makes the system heavier.
This was also a question I had when looking at @0G_labs. They are doing modular design, breaking different functions into separate parts, which in theory can improve efficiency.
But the real issue is, the more modules there are, the higher the coordination costs, and the greater the demands on developers.
If the barrier to entry is too high, even the best architecture will be hard to adopt widely.
On the other hand, this kind of splitting can also bring a benefit: each layer can be optimized independently rather than being constrained by the whole.
So the key isn’t modularity itself, but whether standards can be established.
Without standards, it’s just complex. With standards, it could become the foundational infrastructure of the future.
Many people are now discussing whether it’s the next hot topic, but what really matters is whether it can become an indispensable layer for others.
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