#opg $OPG
@OpenGradient The core idea is that verifying AI inference does not require restarting it, as OpenGradient supports multiple verification methods depending on the risk analysis of the workload. Verified trusted execution environment certificates (TEEs) prove that the deployed software code was executed inside a protected device without tampering.
The network can also generate zero-knowledge proofs (XKML), which cryptographically prove that the correct model produced the correct outputs for specific inputs.
The third option is signature-based verification, which is designed for low-risk workloads.
Developers choose the verification level that matches their specific use case.
$OPG is the project code and the governance token code for network @OpenGradient .
@OpenGradient The core idea is that verifying AI inference does not require restarting it, as OpenGradient supports multiple verification methods depending on the risk analysis of the workload. Verified trusted execution environment certificates (TEEs) prove that the deployed software code was executed inside a protected device without tampering.
The network can also generate zero-knowledge proofs (XKML), which cryptographically prove that the correct model produced the correct outputs for specific inputs.
The third option is signature-based verification, which is designed for low-risk workloads.
Developers choose the verification level that matches their specific use case.
$OPG is the project code and the governance token code for network @OpenGradient .