AI is now incredibly popular, generating text, art, and even code has become the norm. But with this come questions: how do we validate the results of AI? Is the answer from a model reliable? Almost no one can confirm it 100%. This makes the combination of AI and blockchain seem more like a gimmick than a practical technological path.
The technology from Succinct Labs offers a new way to tackle this problem. One powerful capability of zero-knowledge proofs is that they can generate a concise proof for complex computation processes. This means that even if an AI model has run hundreds of millions of calculations, the result can still be confirmed with a small proof file that it was indeed computed in that way. The verifier does not need to repeat the entire computation to ensure that the result has not been tampered with.
This is of great significance for the future of decentralized AI networks. For instance, in a decentralized AI platform, users can submit computational tasks, and after the AI nodes complete them, they return results along with a proof. Users can confirm the results are authentic and trustworthy by simply verifying the proof, without worrying about nodes cheating.
What’s even more interesting is that this approach can make AI no longer a black box. Because every step of the result can be verified, the transparency of AI is greatly enhanced. This not only boosts user trust in AI but also promotes the deep integration of Web3 and AI. It can be said that Succinct Labs' zero-knowledge proofs are like a key that opens the door to trust in AI.
