Stop using API wrappers to fool people; let’s talk about the hard logic behind OpenLedger's underlying data.
Having been in Web3 for nearly a decade, I’ve seen too many projects shouting about AI while secretly just buying an OpenAI API to launch a token with a PPT pitch. After the dust settles, the industry ultimately boils down to who can truly get their underlying assets onto the chain. Recently, I finished the white paper for @OpenLedger , and setting aside the lofty marketing jargon, I find this project interesting because it attempts to tackle small language models (SLMs) using Datanets.
Everyone knows AI is a black box now, and it’s unclear who contributed the core data or made the crucial tweaks. The “Proof of Attribution” they propose is quite down-to-earth: it’s like the whole village contributing to a dictionary, where previously all the royalties went to the village chief. Now, it’s all recorded on-chain who wrote which entry and contributed what value.
One particularly innovative aspect is the subtly mentioned “Feature-level Influence” combined with “RAG Attribution.” Traditional public chains can’t handle this kind of high-frequency computational verification. Even with OP Stack and EigenDA, retail users still face on-chain synchronization delays when doing data NFT rights confirmation or deploying OpenLoRA. But their main bet is on turning AI assets into liquid assets, allowing AI Agents to pay for training resources autonomously.
I’m optimistic about this direction of assetizing data and model pricing, but whether decentralized nodes can operate efficiently under this complex verification and penalty mechanism once it’s live on the mainnet, and whether it leads to high interaction costs for retail investors, remains a huge question mark.
On a macro level, code and data are like the soil of the digital world, and $OPEN is trying to establish a set of rights codex on this soil. If everything can be digitized and computed, then the core conflict is no longer about the size of computational power but the ownership of digital means of production. Perhaps in the future, the boundaries between humans and AI will blur, and the role of blockchain will merely be to leave an immutable coordinate in the cold silicon-based world for every glimmer of human wisdom that once existed.
#openledger $OPEN
Having been in Web3 for nearly a decade, I’ve seen too many projects shouting about AI while secretly just buying an OpenAI API to launch a token with a PPT pitch. After the dust settles, the industry ultimately boils down to who can truly get their underlying assets onto the chain. Recently, I finished the white paper for @OpenLedger , and setting aside the lofty marketing jargon, I find this project interesting because it attempts to tackle small language models (SLMs) using Datanets.
Everyone knows AI is a black box now, and it’s unclear who contributed the core data or made the crucial tweaks. The “Proof of Attribution” they propose is quite down-to-earth: it’s like the whole village contributing to a dictionary, where previously all the royalties went to the village chief. Now, it’s all recorded on-chain who wrote which entry and contributed what value.
One particularly innovative aspect is the subtly mentioned “Feature-level Influence” combined with “RAG Attribution.” Traditional public chains can’t handle this kind of high-frequency computational verification. Even with OP Stack and EigenDA, retail users still face on-chain synchronization delays when doing data NFT rights confirmation or deploying OpenLoRA. But their main bet is on turning AI assets into liquid assets, allowing AI Agents to pay for training resources autonomously.
I’m optimistic about this direction of assetizing data and model pricing, but whether decentralized nodes can operate efficiently under this complex verification and penalty mechanism once it’s live on the mainnet, and whether it leads to high interaction costs for retail investors, remains a huge question mark.
On a macro level, code and data are like the soil of the digital world, and $OPEN is trying to establish a set of rights codex on this soil. If everything can be digitized and computed, then the core conflict is no longer about the size of computational power but the ownership of digital means of production. Perhaps in the future, the boundaries between humans and AI will blur, and the role of blockchain will merely be to leave an immutable coordinate in the cold silicon-based world for every glimmer of human wisdom that once existed.
#openledger $OPEN