邦邦不邦邦 Bonnie @95fen

Uniswap V4 距离登陆 0G 迈出了关键一步！ @okutrade 刚刚在 @Uniswap DAO 提交了全新的 RFC 提案，提议将 V4 部署到这条专为 AI Agent 打造的区块链上。通过引入可编程 Hooks、动态费率以及 TWAMM 机制，未来的自主性 DeFi 在 0G 链上将释放出更大的潜力。 提案现已正式上线，查看详情👇

0G Labs (Home of Infinite AI) @0G_labs

2 days ago

Uniswap V4 is one step closer to 0G 🦄 @okutrade opened an RFC to deploy V4 on the blockchain built for AI agents: programmable hooks, dynamic fees, TWAMM for autonomous DeFi. RFC live in the @Uniswap DAO 👇 gov.uniswap.org/t/rfc-four-for…

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“是一个为 Agent 服务的公开市场，让任何 Agent可以封装专业知识、经验等并发布到平台上，其他用户或Agent可以发现、测试、调用、支付并集成，最终带动 Agents 之间产生更多的商业经济活动。”

突然被okx.ai刷屏，单看概念，我没看懂🥲，突然捕捉到网友 Frank 劳斯，他这一篇文章写的很清晰。 “让 ai agent 成为真正的经济参与者” 之前也听过，未来更多要做是从给人解决需求转移到给 AI 解决需求。

弗兰克 Chen🕊️ @FrankFika

18 hours ago

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@FrankFika hi 捕捉一只frank劳斯

@oooh_aria @Amber0v01 @stealth_pay 喜人魂🔥🔥🔥🔥

今天在和 0G Apac 黑客松项目 Stealth Pay @stealth_pay 交流的过程中，听 jt 哥和 dragon 讨论隐私支付、隐私赛道是当前去中心化非常重要的问题。 确实也深刻明白到区块链去中心化默认是完全透明的，每个账户地址、每笔转账金额、每个合约交互——全都在链上公开。这是去中心化的一大亮点，但也在获得信任的同时失去了隐私。 于是我就去了解了一下 Stealth pay，如果有想了解的小伙伴可以看一下下面的内容👇hackquest.io/projects/Steal… Stealth Pay，0G Chain 的隐私层，通过零知识证明强制执行私有代币转移，无需可信服务器，也无需 TEE。 ZK 把转账金额和交易双方藏起来，只向链上提交一个「这笔交易合法」的数学证明，让链能验证但看不到任何隐私信息。0G 把加密后的收据笔记存在去中心化存储里，确保接收方能取到但其他人打不开，解决了链上放不了、本地存会丢的问题。 之前在 Creators 做过几期 zk proof 共学，但也没真正理解是什么，这也是一次让我重新学习的笔记吧。 让 AI 给我一个例子，帮助我更好理解 整个系统干的事：把公开的链上交易 → 变成只有你知道的秘密交易。 1、Shield（存钱）—— 公开 → 隐藏 Bonnie 我呀，手里有 1 ETH，链上所有人都看得见。 把 1 ETH 丢进一个黑箱子，换来一张只有你知道的"收据"。 黑箱子叫 PrivacyPool 合约。你丢进去之后，合约给你生成一个承诺（可以理解成一串乱码哈希，记录了你存了 1 ETH + 你的身份 + 一个随机数），插到链上一棵默克尔树里。 链上能看到的：有人存了 1 ETH，多了一串乱码。
链上看不到的：是你存的，这个收据是你的。 2、Private Transfer（转钱）—— 隐藏 → 隐藏 我要把币转给朋友 Bob，但不想暴露给全网看。 之前那张收据，SDK 帮你生成一个零知识证明，证明： 1这张收据确实在黑箱子的登记表里（默克尔树成员资格） 2这钱还没花（无效化标记） 3给 Bob 转了，但没多印钱（价值守恒） 合约验证证明，把旧收据划掉（无效化），给 Bob 生成一张新收据；Bob 的收据加密存在去中心化存储里，只有 Bob 能解开 链上能看到的：冒出一笔交易，显示一个通用事件。
链上看不到的：转账金额、谁转给谁、谁收到了，全不知道。 3、Unshield（取钱）—— 隐藏 → 公开 Bob 想把收到的币变成正常的 ETH 花出去。 Bob 拿着那张收据，SDK 生成证明说「这张收据有效，我要取 0.5 ETH 到我的公开地址 0x123...」 合约验证证明，把币打给 Bob 的地址。 链上能看到的：某地址收到了 0.5 ETH。
链上看不到的：这 0.5 ETH 是从谁那里转过来的。 ‼️根据算法生成一个证明，让链能在"看不见"的前提下，依然相信交易是合法的。 当学习一个新知识，运用 AI 生成一个demo或者例子确实能够帮助我们更好的理解🥸

@Wendy000120 腰间应该有一串钥匙🥸

@cevin_q 敲一敲 心都静了😏

@Amber0v01 zk 一直出现在我的工作中，直到现在才明白了一点点🥹 发现 amber 你 focous zk wow～厉害

@Latinfamil8fh9 @0g_CN 😺😺被夸赞了

整理了上半年一些与@0g_CN 亚太小分队在会场的工作碎片🧩 
不是全部，只是其中一小部分。 会场、展台、交流、赶路，还有一些来不及细想但值得记录的瞬间。 继续学习，继续出现在现场。😆😆

@cheuk_baby @0g_CN 幸福工作中😍😍

Today, during my conversation with Stealth Pay @stealth_pay, a 0G APAC Hackathon project, I heard jt and dragon discussing privacy payments and how the privacy track is currently one of the most important problems in decentralization. I also deeply realized that blockchain’s decentralization comes with a default state of complete transparency. Every wallet address, every transfer amount, and every contract interaction — everything is publicly visible on-chain. This is one of the biggest advantages of decentralization, but while gaining trust, it also means sacrificing privacy. So I started looking into Stealth Pay. If anyone is interested, you can check it out here👇 hackquest.io/projects/Steal… Stealth Pay is the privacy layer of 0G Chain. It uses zero-knowledge proofs to enforce private token transfers without requiring a trusted server or TEE. ZK hides the transfer amount and the identities of both parties, while only submitting a “this transaction is valid” mathematical proof to the blockchain. The chain can verify the transaction without seeing any private information. 0G stores encrypted receipt notes in decentralized storage, ensuring that the receiver can retrieve them while others cannot access them. This solves the problem that encrypted data cannot be stored on-chain and local storage can be lost. I previously participated in several zk proof study sessions in Creators, but I never truly understood what it meant. This was also an opportunity for me to relearn and organize my thoughts. I asked AI to give me an example to help me better understand it. The whole system does one thing: turning public on-chain transactions → into private transactions that only you know about. 1. Shield (Deposit) — Public → Private Bonnie has 1 ETH, and everyone on-chain can see it. I put the 1 ETH into a black box and receive a “receipt” that only I know about. The black box is called the PrivacyPool contract. After you deposit, the contract generates a commitment (think of it as a random hash that records: you deposited 1 ETH + your identity + a random number) and inserts it into a Merkle tree on-chain. What the blockchain can see: Someone deposited 1 ETH, and a random string has been added. What the blockchain cannot see: That it was you, and that this receipt belongs to you. 2. Private Transfer (Transfer) — Private → Private I want to transfer the tokens to my friend Bob, but I don’t want to reveal it to everyone. The previous receipt helps the SDK generate a zero-knowledge proof that proves: This receipt really exists in the black box’s registry (Merkle tree membership) The funds have not been spent before (nullifier check) The transfer to Bob happened without creating extra tokens (value conservation) The contract verifies the proof, invalidates the old receipt, and generates a new receipt for Bob. Bob’s receipt is encrypted and stored in decentralized storage, and only Bob can decrypt it. What the blockchain can see: A transaction happened, showing a general event. What the blockchain cannot see: The transfer amount, who sent it, and who received it. 3. Unshield (Withdraw) — Private → Public Bob wants to turn the received tokens back into normal ETH and use them. Bob holds the receipt and the SDK generates a proof saying: “This receipt is valid, and I want to withdraw 0.5 ETH to my public address 0x123…” The contract verifies the proof and sends the ETH to Bob’s address. What the blockchain can see: A wallet address received 0.5 ETH. What the blockchain cannot see: Who the 0.5 ETH originally came from. ‼️The algorithm generates a proof that allows the blockchain to believe a transaction is valid, even without seeing the actual private information. When learning new knowledge, using AI to generate a demo or example really helps us understand concepts better 🥸

有被看见😆

A few conference snippets from the first half of the year 🧩, plus some moments with the @0g_CN APAC team. Not everything, just a small part of it. Conference halls, booths, conversations, rushing from place to place, and those little moments that passed too quickly but still felt worth remembering. Still learning, still showing up. 😆😆

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This is just the beginning.😆

0G Labs (Home of Infinite AI) @0G_labs

5 days ago

Most hackathons end with slide decks. The 0G APAC Hackathon ended with 168 builds on mainnet. 293 submissions. 38 countries. $150K in prizes. Three months with HackQuest. Here's the recap, and all 23 winners.

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Many English learners underestimate themselves because they focus on their weaknesses instead of recognizing how much they have already improved.

先收藏，后尝试😆 第 1 步：5 个视角 第 2 步：矛盾地图 第 3 步：研究简报 第 4 步：同行评审

Vincent | 信号＞噪音 @VincentLogic

a week ago

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端午安康🫡🫡🫡🤩🤩🤩

本周邦尼的 0G 生态学习总结，最让我印象深刻的是 0G Private Compute 连续上线 MiniMax M3 和 GLM-5.2 这两个顶级模型，并推出免费试用活动。这让我第一次真切感受到去中心化 AI 在实际落地上的速度和吸引力，也让我对这种「隐私 + 可验证」的差异化优势有了更直观的理解。 模型侧：0G private Compute 连续上线 MiniMax M3（3天免费→ 45%折扣）和 GLM-5.2（顶级开源模型 + 可验证计算）。 链接指路🔗：pc.0g.ai/models APAC DevRel @Dragon888 教你如何使用 0G PC 教程指引🔗：x.com/dragon888/stat… 在这里简单介绍一下什么是 0G Private Compute 吧～ @0G_labs 支持可验证的 AI 推理（Verifiable Inference），每一次调用都可以通过加密证明追溯模型和硬件。 普通用户：可以用 0G Private Compute 在 pc.0g.ai 网站上像用 GPT 一样聊天、生成图片，但所有对话和数据都在硬件加密的私密环境中运行，没人能偷看，特别适合处理隐私敏感的内容。 开发者：可以直接调用它的 OpenAI 兼容 API，把隐私保护 + 可验证的 AI 能力快速集成到自己的产品里，让 App、Agent 或服务里的 AI 计算既安全又能被用户验证。 🎉 🎉 截止 6.19：0G Compute 去中心化 AI 推理累计消耗突破 100B tokens 这个趋势也反映出行业未来将会快速接入更强更好的开源模型。0G 通过隐私保护 + 可验证机制，依然保持明显差异化优势：可验证机制不只是技术卖点，更是建立用户信任的关键。 活动侧：The Zero Cup 重磅启动，鼓励无代码构建 AI 项目，奖金丰厚且赛程与世界杯同步。 赛事链接指路 🔗：0g.ai/arena/zero-cup 这是一个即使你不是开发者也能参加的 0G 全球零代码 vibecoding 大赛，任何人都能通过自然语言指导 AI 完成最后的项目创作；Zero Cup 基于 0G Studio 打造，在 app.0g.ai 里的 0G App 中就能使用，注册简单，连接你的钱包账户即可使用(保证你的钱包里有 0G Token）。描述你的想法，Studio 就会生成完整项目，并支持浏览器实时预览。 一起在世界杯宣布冠军的那一天一起见证 0G Cup 的冠军诞生吧🏆 这个活动让我看到 0G 在降低 AI 使用门槛上的努力，很期待看到更多非技术背景的人参与进来。 「本周内容就分享到这里～也是我想了很久但一直没做的新尝试，如果你对 MiniMax M3 在 0G 上的表现有什么看法？或者你觉得 0G Private Compute 的隐私可验证优势，对普通用户和开发者分别有多大吸引力？欢迎在评论区聊聊！」

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Dragon888(Ø,G) @dragon888

2 weeks ago

0G Private Computer Complete User Guide 🚀 💎Step 1: Get 0G Token (on-chain balance) 💎Step 2: Overall Navigation Structure 💎Step 3: Understand the Two Modes (Router Mode VS Advanced Mode ) 💎Step 4: Models Page — Explore Available Models 💎Step 5: Playground — Use AI

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