#opg $OPG
@OpenGradient
What is OpenGradient?
OpenGradient is a decentralized infrastructure network that allows for AI operations, deploying agents, launching applications, and securely hosting AI models in a verifiable manner.
Its official site describes it as the open intelligence network, highlighting its support for verifiable high-performance computing for AI.
This project is based on the hybrid AI computing architecture from OpenGradient.
The official documentation clarifies that "inference nodes" run the models, while "full nodes" handle proof verification and maintain the ledger, providing "data nodes" with reliable access to external information, and "off-chain storage" ensures the availability of extensive model data and proofs without overloading the chain.
The main technical pillars of the platform are as follows:
• Verifiable AI execution: OpenGradient supports TEE certificates, ZKML proofs, and signature-based verification, allowing developers to choose the integrity model best suited for each AI workload.
• Model hosting and developer tools: The documentation highlights the decentralized "Model Hub," a Software Development Kit (SDK) in Python, and secure inference in large language models (LLM).
• Specialized AI computing architecture: HACA separates model execution from validation.
@OpenGradient
What is OpenGradient?
OpenGradient is a decentralized infrastructure network that allows for AI operations, deploying agents, launching applications, and securely hosting AI models in a verifiable manner.
Its official site describes it as the open intelligence network, highlighting its support for verifiable high-performance computing for AI.
This project is based on the hybrid AI computing architecture from OpenGradient.
The official documentation clarifies that "inference nodes" run the models, while "full nodes" handle proof verification and maintain the ledger, providing "data nodes" with reliable access to external information, and "off-chain storage" ensures the availability of extensive model data and proofs without overloading the chain.
The main technical pillars of the platform are as follows:
• Verifiable AI execution: OpenGradient supports TEE certificates, ZKML proofs, and signature-based verification, allowing developers to choose the integrity model best suited for each AI workload.
• Model hosting and developer tools: The documentation highlights the decentralized "Model Hub," a Software Development Kit (SDK) in Python, and secure inference in large language models (LLM).
• Specialized AI computing architecture: HACA separates model execution from validation.