Many AI projects, when discussing Web3 narratives, actually overlook a real issue.

The operating costs of AI are very high.
Model inference requires computing power, and large amounts of data need to be stored, but today these resources are mostly controlled by a few cloud service providers.
If Web3 wants to truly participate in the AI industry, it must offer an alternative infrastructure option.
This is exactly the problem @0G_labs aims to solve.
They are building a decentralized AI network that allows computing nodes, storage nodes, and developers to collaborate within the same ecosystem.
Computing resources and data storage are no longer dependent on a single platform but are provided collectively by network participants.
The changes brought by this model are not just technical.
When computing power, storage, and data start being distributed through open networks, the barrier to AI application development will significantly decrease.
Developers will no longer need to rely entirely on traditional cloud services to deploy their systems.
From an industry perspective, this is a new infrastructure logic.
If AI applications become widespread in the future, the computing power and data resources provided by decentralized networks could become an important supplement to the entire ecosystem.
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