$ETH Unpacking the facade of "verifiable AI": Is on-chain computation really a false proposition?
The buzz in the scene is all about "decentralized AI", with various PPT projects popping up everywhere. To put it bluntly, it's just a bunch of hype-driven schemes that slap an API on and claim to be Web3 AI—complete nonsense. Today I stumbled upon @OpenGradient , and finally saw a project with a solid problem-solving approach. These folks aren't getting caught up in those nebulous Agent gimmicks; they're going straight for the infrastructure, working on on-chain AI models and verifiable computation, which is quite intriguing.
Breaking down $OPG , the core logic is making the computation process "provable". Most of those working on AI chains are still stuck in the dead end of how to stuff massive model parameters onto the chain. In contrast, this team has created an EVM-compatible network that uses zkML proofs plus TEE validation. This is actually quite clever, avoiding the catastrophic latency of full on-chain computation and using off-chain computation with on-chain verification instead. Their website claims they've executed 2 million verification inferences, and if that number is legit, their engineering capabilities are something to note, as many public chains struggle to run larger smart contracts.
What they're developing, the OpenGradient Chat, is a true litmus test of their capabilities. Nowadays, privacy chat tools are a dime a dozen, but there aren't many genuinely branded as "AI privacy infrastructure". The pain point is clear: institutional players need to leverage AI for quantitative analysis and research reports, but would never dare feed their core strategies and trump cards to OpenAI. Creating verifiable and tamper-proof localized or decentralized nodes for processing is logically sound. Compared to those air coins that only issue PR after securing funding, bringing in a16z and Coinbase for support, and joining Nvidia's startup program, at least it shows that their narrative and technical foundation can pass muster with top-tier VCs. As for that BitQuant, claiming to be building on-chain quantitative AI, if they can indeed run a verifiable risk prediction model to optimize AMM liquidity pools, then the DeFi game might just be set for a serious evolution. This project is worth keeping an eye on to see how the mainnet performs. #OPG
Putting airdrop points aside, can this seamless model-shifting decentralized AI routing really take down the API hegemony of the big players?
The buzz in the scene is all about "decentralized AI", with various PPT projects popping up everywhere. To put it bluntly, it's just a bunch of hype-driven schemes that slap an API on and claim to be Web3 AI—complete nonsense. Today I stumbled upon @OpenGradient , and finally saw a project with a solid problem-solving approach. These folks aren't getting caught up in those nebulous Agent gimmicks; they're going straight for the infrastructure, working on on-chain AI models and verifiable computation, which is quite intriguing.
Breaking down $OPG , the core logic is making the computation process "provable". Most of those working on AI chains are still stuck in the dead end of how to stuff massive model parameters onto the chain. In contrast, this team has created an EVM-compatible network that uses zkML proofs plus TEE validation. This is actually quite clever, avoiding the catastrophic latency of full on-chain computation and using off-chain computation with on-chain verification instead. Their website claims they've executed 2 million verification inferences, and if that number is legit, their engineering capabilities are something to note, as many public chains struggle to run larger smart contracts.
What they're developing, the OpenGradient Chat, is a true litmus test of their capabilities. Nowadays, privacy chat tools are a dime a dozen, but there aren't many genuinely branded as "AI privacy infrastructure". The pain point is clear: institutional players need to leverage AI for quantitative analysis and research reports, but would never dare feed their core strategies and trump cards to OpenAI. Creating verifiable and tamper-proof localized or decentralized nodes for processing is logically sound. Compared to those air coins that only issue PR after securing funding, bringing in a16z and Coinbase for support, and joining Nvidia's startup program, at least it shows that their narrative and technical foundation can pass muster with top-tier VCs. As for that BitQuant, claiming to be building on-chain quantitative AI, if they can indeed run a verifiable risk prediction model to optimize AMM liquidity pools, then the DeFi game might just be set for a serious evolution. This project is worth keeping an eye on to see how the mainnet performs. #OPG
Putting airdrop points aside, can this seamless model-shifting decentralized AI routing really take down the API hegemony of the big players?
能，聚合路由是刚需
0%
悬，拼不过大厂算力
50%
观望，先撑住高并发
50%
2 votes • Voting closed