Decentralized AI has finally reached that "aha moment"—

Running a 10-billion-parameter model on a single consumer-grade GPU? And it even comes with cryptographic proofs? This was unimaginable before.

In the past, AI inference was a dead loop: either you spent big bucks on black-box services from centralized platforms, handing over all your models and data, or you worried about your data being leaked or tampered with. Either way, you had no choice.

Now, some teams are using technology to completely overturn this setup. The core of their solution can be summed up in one word: decomposition.

Break the large model inference task into countless small pieces and distribute them to ordinary GPUs in a decentralized network. Each node only sees a fragment of the task and cannot reconstruct the full data; after computation, it signs the result cryptographically to prove, "This is the result I genuinely computed—no tampering."

Let’s skip the technical details for now—the key point is the lower barrier to entry. That 3090 sitting idle at home can now join the network, participate in inference, and even earn some rewards.

This is what true decentralization should look like: no reliance on tech giants, no sacrifice of privacy, and a return of computing power to the people.