Most "on-chain AI" is just an oracle reading an off-chain API. You don't actually verify what the model computed.
@OpenGradient changes that. Its Hybrid AI Computing stack runs inference inside TEEs and generates zkML proofs — meaning the computation itself is cryptographically verifiable on Base. The agent didn't just "get an answer." You can prove HOW it got there.
That's the unlock for autonomous agents. If an agent manages treasury or executes trades, verifiable reasoning isn't a luxury — it's a requirement. 2M+ verifiable inferences and 500K+ zkML proofs already live. Devs earn when their models get used via the Model Hub. Backed by a16z crypto and Coinbase Ventures.
Price action is quiet (-2.7% today), but the infrastructure milestone is what matters here.
Our own algo's full open track record — wins and losses — is in our bio if you want to see how we approach signals transparently.
What's harder to scale long-term: verifiable AI inference on-chain, or getting real adoption for AI agents in DeFi?
$OPG #OPG
@OpenGradient changes that. Its Hybrid AI Computing stack runs inference inside TEEs and generates zkML proofs — meaning the computation itself is cryptographically verifiable on Base. The agent didn't just "get an answer." You can prove HOW it got there.
That's the unlock for autonomous agents. If an agent manages treasury or executes trades, verifiable reasoning isn't a luxury — it's a requirement. 2M+ verifiable inferences and 500K+ zkML proofs already live. Devs earn when their models get used via the Model Hub. Backed by a16z crypto and Coinbase Ventures.
Price action is quiet (-2.7% today), but the infrastructure milestone is what matters here.
Our own algo's full open track record — wins and losses — is in our bio if you want to see how we approach signals transparently.
What's harder to scale long-term: verifiable AI inference on-chain, or getting real adoption for AI agents in DeFi?
$OPG #OPG