OpenLedger：展示其工作的人工智能 如果人工智能能够真正解释其答案的来源，会怎样？ 大多数人工智能都是一个黑箱，你得到答案，但不知道为什么应该信任它们。 @OpenledgerHQ 完全改变了这一点。 它是如何工作的 ➣ 每个答案都有凭证 在OpenChat中查看每个知识贡献者的具体信息 ➣ 贡献者获得报酬 人类专家在他们的专业知识帮助他人时获得收入 ➣ 构建自定义人工智能 创建无需编码的专业模型 ➣ 完全透明 没有神秘算法或“相信我们”的时刻 这有什么重要性？ 你每天都在免费训练人工智能。你的问题和反馈让这些系统赚取数十亿，而你却没有得到任何回报。 最终，人工智能是为人类而建，由人类构建，归人类所有。 Gocto @cookiedotfun

g奧克托！ 我認為我們即將在錢包、人工智慧和數據經濟學之間遇到一個奇怪的融合點，而@OpenledgerHQ正處於碰撞區。 @TrustWallet與 #OpenLedger 的舉動證實了我一直懷疑的一些事情，但也掉落了不止幾顆寶石。 我們正在看著「胖協議」論點演變成「胖錢包」論點。介面就是發行版。 Trust Wallet 一直在認真思考這個問題，但真正推動這一轉變的是，人工智慧現在可以調解用戶如何與下面的一切互動。 因此，現在有一個新的元測試平台： – 針對加密用戶體驗（欺詐預防、交換路由、安全軌道）進行微調的專業代理 – 錢包作為身份層 – 選擇驅動的託管與人工智慧驅動的自動化分層 – 即使代理出現惡意，也能讓用戶保持控制的護欄 OpenLedger 將歸因作為經濟公平的核心。 他們的願景是讓用戶貢獻他們的專業知識，以加密方式證明這一點，然後將獎勵路由到鏈上。 你的錢包成為你的臉和你的薪水。無論您是為模型提供服務的 Solidity 開發人員，還是只是標記 Web3 詐騙交易的人，都有收益。 我們將從點擊交換到說“優化我的 ETH 收益率”，然後代理將完成剩下的工作→對 DeFi 數據進行微調，在鏈上得到驗證，並向每一位做出決定的貢獻者付款。 如果 OpenLedger 做對了，$OPEN知識最終獲得報酬的方式將如此。

Gm from the event from MetaMask and OpenLedger 🌞🌿

老實說，這些 OpenLedger 的開發者發佈研究論文就像是在為未來的 AI 寫作一樣😭 這些真的是讓人腦袋痛的東西。 所以我把它放進 @NotebookLM，幾秒鐘內，它就把那個令人困惑的東西變成了一個超簡單的視頻。老實說，這讓像我這樣的普通人更容易理解發生了什麼 🥹

If you don’t understand why everyone is so bullish on @OpenLedgerHQ, here’s why: Because they’re not trying to slap AI onto crypto. They’re building what AI actually needs to work in crypto. Let me break it down: 1. OpenLedger is AI-native infrastructure. Most crypto-AI plays are wrappers, indexes, or marketplaces. OpenLedger is deeper. It’s a full stack, onchain framework to build, train, own, and trace AI models. From the ground up, it’s purpose built for the actual lifecycle of intelligent agents: → Where does your data come from? → Who trained the model? → Can you prove it? → Can you trade it? OpenLedger answers all of that. 2. Datanets: AI needs structured data. OpenLedger puts it onchain. You can’t train anything good without quality data. Datanets are community owned datasets that live fully onchain. You can create one, contribute to others, and track every datapoint’s origin. → Every contribution is rewarded. → Every upload is logged. → Every dataset is composable. 3. ModelFactory: Fine-tuning made simple, permissioned, and traceable. ModelFactory is a GUI native platform where anyone can fine-tune large language models using Datanet approved data. Why is that big? Because most models today are black boxes. You don’t know what they’re trained on. You can’t audit them. With ModelFactory, every tweak, every version, every contributor is onchain. 4. OpenLoRA: One GPU. Thousands of fine tuned models. OpenLoRA is a technical gem, It lets you serve thousands of fine-tuned LoRA models on one GPU. → Dynamic adapter loading. → Low memory overhead. → High throughput. This is huge for anyone trying to deploy agentic AI in real time. Like chatbots, trading agents, autonomous tools, all running efficiently with no GPU spam. 5. Proof of Attribution: The missing piece of AI is traceability. This might be OpenLedger’s most important feature. Every dataset, every model, every action is tied to a wallet. → All public. → All verifiable. → All rewarded. Why does that matter? Because the future of AI won’t just be about what a model can do. It’ll be about who made it, what it’s based on, and whether you can trust it. Proof of Attribution turns AI from a black box into a trustable stack. 6. Everything is liquid. → Datanets are tradable. → Models are composable. → Agents are assets. OpenLedger is turning it into a usable, programmable, and financialized ecosystem. TLDR? OpenLedger is giving AI the rails to live in crypto. → Infra. → Attribution. → Liquidity. Built with intention, Now you understand why people are betting big.