#opg During this period, I’ve been researching how to consistently monetize idle computing power. I’ve basically gone through almost all the verifiable computing projects on the market, and to be honest, most of them are just old套路 with a new skin—there isn’t much real technical innovation. It wasn’t until I carefully studied the underlying architecture of @OpenGradient that I realized it truly has something.
Its most core highlight is that it completely separates computation and verification. In a traditional public chain, when running AI inference, all nodes across the network repeat the computations, which is extremely wasteful of resources. OPG, on the other hand, has a node complete the model inference on its own, then only uploads the final proof on-chain. The chain is only responsible for verifying whether the result is correct. This cuts out most of the redundant costs, and the advantage over similar projects is very obvious.
I also personally tested it on the testnet and ran a few rounds of AI inference tasks. Overall, the asynchronous settlement process is very smooth. For players who use common scripts and node-bot integrations to interact with the chain, the practicality is maxed out. It can ensure that nodes are running open-source, transparent code, eliminating the risk of stealthy backdoor changes and permission theft—security is clearly visible.
But having solid technical logic doesn’t mean there’s no risk in real-world deployment. Its current security foundation heavily depends on trusted hardware execution environments. Anyone who understands security testing knows that this kind of hardware foundation has had quite a few vulnerabilities in the past. If the hardware protections are ever compromised, then relying solely on zero-knowledge proofs to underwrite verification of model inference tasks would cause costs to skyrocket by dozens of times or more. In that scenario, the entire network would very likely become congested and crippled.
Also, as a computing power provider, what I care about most is truly stable returns. High-end GPU electricity costs and depreciation are not cheap. If the node revenue of $OPG can’t outperform ordinary cloud computing rental platforms, miners probably won’t stick around—they’ll likely just shut down and unplug. Right now, the project’s penalty and forfeiture rules, as well as the revenue model, haven’t been fully disclosed, so the economic system is still an unknown.
Even if the testnet data looks good, it’s still virtual—it’s only a simulation. I’m keeping an observation stance and absolutely not going in with a heavy position. Once the mainnet launches and real demand steadily increases, and when miners’ true payback period and daily revenue data are fully transparent, then entering the market would be the safest choice. For now, I’ll just wait for the official release of the real node revenue calculation data. $BTC $SPCXB
Its most core highlight is that it completely separates computation and verification. In a traditional public chain, when running AI inference, all nodes across the network repeat the computations, which is extremely wasteful of resources. OPG, on the other hand, has a node complete the model inference on its own, then only uploads the final proof on-chain. The chain is only responsible for verifying whether the result is correct. This cuts out most of the redundant costs, and the advantage over similar projects is very obvious.
I also personally tested it on the testnet and ran a few rounds of AI inference tasks. Overall, the asynchronous settlement process is very smooth. For players who use common scripts and node-bot integrations to interact with the chain, the practicality is maxed out. It can ensure that nodes are running open-source, transparent code, eliminating the risk of stealthy backdoor changes and permission theft—security is clearly visible.
But having solid technical logic doesn’t mean there’s no risk in real-world deployment. Its current security foundation heavily depends on trusted hardware execution environments. Anyone who understands security testing knows that this kind of hardware foundation has had quite a few vulnerabilities in the past. If the hardware protections are ever compromised, then relying solely on zero-knowledge proofs to underwrite verification of model inference tasks would cause costs to skyrocket by dozens of times or more. In that scenario, the entire network would very likely become congested and crippled.
Also, as a computing power provider, what I care about most is truly stable returns. High-end GPU electricity costs and depreciation are not cheap. If the node revenue of $OPG can’t outperform ordinary cloud computing rental platforms, miners probably won’t stick around—they’ll likely just shut down and unplug. Right now, the project’s penalty and forfeiture rules, as well as the revenue model, haven’t been fully disclosed, so the economic system is still an unknown.
Even if the testnet data looks good, it’s still virtual—it’s only a simulation. I’m keeping an observation stance and absolutely not going in with a heavy position. Once the mainnet launches and real demand steadily increases, and when miners’ true payback period and daily revenue data are fully transparent, then entering the market would be the safest choice. For now, I’ll just wait for the official release of the real node revenue calculation data. $BTC $SPCXB