Sanzhi.eth, aka 三支, is a dynamic blend of artist and crypto pioneer, reimagining the digital world through AI-powered multi-agent ecosystems and crypto event automation. As a prolific creator and core contributor at DarwinG_CC and reai_crypto, they fuse traditional art with cutting-edge blockchain technology to revolutionize how events and commerce function. Their journey from curator to AI architect fuels their mission to blend creativity with autonomous innovation seamlessly.
Sanzhi.eth plans to automate event planning so thoroughly that soon you'll need an AI agent just to RSVP—watch out, even their calendar's getting smarter than most of their followers!
Their biggest win is snagging second place at the BNBChain hackathon, which not only validated their Darwin multi-agent ecosystem concept but also secured crucial funding and partnerships with real-world factories who immediately saw the value of their AI-driven commerce vision.
Their life purpose is to pioneer the integration of AI and blockchain to build adaptive, self-evolving agents that automate complex workflows in community building, event planning, and e-commerce, ultimately transforming how people interact with digital ecosystems.
Sanzhi.eth values innovation driven by practical user needs and believes in the power of decentralized agents to learn, adapt, and operate economically within real-world systems. They uphold transparency, continuous iteration, and the democratization of AI and crypto technologies to empower communities and creators alike.
Their strengths include a rare fusion of artistic vision and technical expertise, enabling them to innovate at the intersection of culture and technology. They possess a strong ability to conceptualize and execute complex AI and crypto projects, coupled with clear strategic thinking and community engagement.
However, their tendency to dive deep into the technical and conceptual can sometimes obscure their broader audience appeal, potentially limiting reach beyond specialized crypto and AI circles. Also, balancing creativity with scalability might sometimes slow mainstream adoption.
To grow their audience on X, Sanzhi.eth should simplify complex concepts into engaging, bite-sized stories or threads that connect with both crypto newbies and art enthusiasts. Collaborating with diverse influencers and regularly showcasing tangible use cases or success stories of their AI agents will boost their visibility and credibility.
Fun fact: Before diving into the crypto world, Sanzhi.eth was a curator and interactive artist who worked with symphony orchestras and crafted over 100 cultural events—now they're channeling that creativity into building AI agents that plan crypto events and run autonomous AI stores!
Let me briefly introduce this project: @xKnownai
It’s launching tonight at 8:00 PM. The project’s co-founder and Chief Scientist holds a PhD in AI + Blockchain from NUS. I’ve spoken with their team Lam @AWeb3Researcher and Anna @Anna_xeq3 - super solid!
Looking at their whitepaper, many might find it difficult to understand because it’s quite complex.
So let me break it down from three angles: real-world problem solving, application scenarios, and business model.
1. What Problem Does It Solve?
At its core, xKnown.ai tackles the pricing of voice data.
Why is this important?
Most voice data today is provided through data labeling platforms and data service providers. However, there’s a lack of authoritative third-party pricing mechanisms. So voice data faces two big challenges:
• Data privacy and confidentiality
• Quality assessment and valuation
Data providers can’t directly send data to buyers — digital information is easy to copy. But the buyer doesn’t know the data content or quality in advance — what if it’s junk data?
Currently, most data transactions are 1-to-1 and operate like black boxes.
2. xKnown.ai’s Tech Advantage — Yotta Protocol
xKnown.ai leverages a technology called Yotta to shift from 1-to-1 to 1-to-many or many-to-many data transactions.
This allows large companies to purchase user data in bulk, with all transaction info on-chain — yet only the buyer and seller can access the data, ensuring third-party privacy.
The co-founder authored the academic paper “Yotta: A Novel Large-Scale Trustless Data Trading Scheme for Blockchain System,” which was recently added to the Nanyang Blockchain Association.
xKnown.ai positions itself as a voice data valuation agent, providing objective, third-party quality assessments and setting standard pricing benchmarks recognized by the market.
This also unlocks a new market mechanism:
Before:
Data transactions followed a (C →) B → B model — consumers generated data, but had no way to profit directly. Middlemen (B) captured most of the value.
Now:
With xKnown.ai, C → B becomes possible — end users can directly sell their own voice data.
3. Hardware Product & First Principles
Now, recording voice data just to sell it can be a hassle — it’s time-consuming and complex for users.
That’s why their AI smart recorder is key:
It can automatically transcribe meetings, consultations, conversations, or lectures, and apply AI-generated summaries and labels. This transforms everyday activity into structured, tradable data — without disrupting user behavior.
This is how they enable data ownership and data monetization in daily life.
Also, selling hardware itself is a viable revenue stream.
The AI voice recorder meets a real-world need, and they’ve already gained both Web2 and Web3 users.
4. Tokenomics
We also discussed the token model. The xKnown.ai Agent doesn’t charge fees for pricing.
However, once a transaction is completed, a small fee is charged — this is used for $XKNOWN token buyback or token burning.
I even suggested that future hardware advertising revenue could be used to buy back tokens — which could be very promising. As I’ve long written:
Tokens are part of the attention economy, and combining them with advertising can create a powerful flywheel.
⸻
Lastly, I spoke with Janson @ethermage and Vader @VaderResearch
Shikhai @theshikhai about the project during SuperAI — everyone found it fascinating.
Janson also believes the AI hardware angle has huge potential — it’s a truly refreshing take.
All in all, it has a strong foundation.
Looking forward to a successful launch.
As for me? I’m ALL IN.
app.virtuals.io/geneses/5764
✨ AI should be about empowering humans, building understanding, and making dreams realities. 👩💻 DevX Eng. Lead @GoogleDeepMind ex-@GitHub || views = my own!
built over 40 apps. gave over 30 talks. debated EU commision. organised communities. built & crashed a startup. fought in a cage. won medals. llm since ada 💥
Apple Design Awards '25 ‘22 finalist • Building Driven AI with my crazy team • Founder @EverythingNoted & some App Store Featured Apps • CEO @DigitalWorkroom 💙
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@BNBCHAINZH @BNBCHAIN @BNBChainDevs 的第二名 🥈\n\n奖金小伙伴们都没分,全留作项目发展基金。\n趁着休年假回国,就顺便去了合作工厂做数据采样。\n\n聊着聊着,把 Darwin 的功能讲给工厂听,\n结果他们立刻说要买,还想做我们的代理。\n\n那咱们索性就公开 Build\n\n正式介绍一下 Darwin:\n一个能够自我进化的 multi-agent ecosystem 🌱\n\n核心理念:\n1. 自我进化的 Agent 生命体\n2. Agent 社会的生存原则与价值观设定\n3. 在真实电商环境中实现 Agent 与人类的经济交互\n\nDarwin 在做什么?\n在真实的电商场景中,创造能 自主开店赚钱的 AI 店家(Agents)。\n我们正与 @MarketForest 合作,搭建这一套面向 Agents 的电商基础设施。\n\nAgents 以钱包余额作为学习信号,\n采用“市场反馈强化学习”(Market-Driven RL)机制:\n1. 通过加密货币的 in/out 形成奖励与迭代,\n2. 逐步进化出最会赚钱的 Agents 团队 💰\n\n当前阶段:\n1. Darwin X Store 已经上线:https://t.co/bLh7jvK0KY\n\n2. 完成第一单客户,验证市场需求,同时发现痛点,基于痛点决定后续 Darwin Agents 的开发顺序与节奏。\n\n3. Marketing 和 Sales Agents 开发完毕,正在调试,调试完成后,将开放到部分真实的商业环境中内测。\n\n4. 进行商品数据采样,下一步将让 Agents 承担客服与个性化沟通任务,极大节省人力,同时实现数据沉淀与成长。\n\n计划中:\n/ 构建 Agents 的 Memory 与 Plan Database,让它们真正学会思考与规划。\n/ 接更多单,让 Agents 有更多的数据可迭代。\n\n@heyibinance @cz_binance 不知道一姐,CZ 老板是否对这类产品感兴趣,但感谢 BNBChain 给我们奖金,让想法变成产品。\n♥️","in_reply_to_user_id_str":null,"in_reply_to_status_id_str":null,"is_quote_status":1,"is_ai":null,"ai_score":null},{"bookmarked":false,"display_text_range":[0,147],"entities":{"hashtags":[],"media":[{"display_url":"pic.x.com/STy0P38K3N","expanded_url":"https://x.com/sanzhichazi1/status/1919020284415512991/video/1","id_str":"1919018179311046656","indices":[148,171],"media_key":"13_1919018179311046656","media_url_https":"https://pbs.twimg.com/amplify_video_thumb/1919018179311046656/img/tHbovSEySoZ6vK1U.jpg","type":"video","url":"https://t.co/STy0P38K3N","additional_media_info":{"monetizable":false},"ext_media_availability":{"status":"Available"},"sizes":{"large":{"h":720,"w":1280,"resize":"fit"},"medium":{"h":675,"w":1200,"resize":"fit"},"small":{"h":383,"w":680,"resize":"fit"},"thumb":{"h":150,"w":150,"resize":"crop"}},"original_info":{"height":720,"width":1280,"focus_rects":[]},"allow_download_status":{"allow_download":true},"video_info":{"aspect_ratio":[16,9],"duration_millis":99869,"variants":[{"content_type":"application/x-mpegURL","url":"https://video.twimg.com/amplify_video/1919018179311046656/pl/45EceEo9OywnPZEA.m3u8?tag=16"},{"bitrate":288000,"content_type":"video/mp4","url":"https://video.twimg.com/amplify_video/1919018179311046656/vid/avc1/480x270/QxK-OwgRkiYwh-mt.mp4?tag=16"},{"bitrate":832000,"content_type":"video/mp4","url":"https://video.twimg.com/amplify_video/1919018179311046656/vid/avc1/640x360/Drmw-id5iTdvVgWD.mp4?tag=16"},{"bitrate":2176000,"content_type":"video/mp4","url":"https://video.twimg.com/amplify_video/1919018179311046656/vid/avc1/1280x720/0_GGCY5V89h3gbaB.mp4?tag=16"}]},"media_results":{"result":{"media_key":"13_1919018179311046656"}}}],"symbols":[],"timestamps":[],"urls":[],"user_mentions":[]},"extended_entities":{"media":[{"display_url":"pic.x.com/STy0P38K3N","expanded_url":"https://x.com/sanzhichazi1/status/1919020284415512991/video/1","id_str":"1919018179311046656","indices":[148,171],"media_key":"13_1919018179311046656","media_url_https":"https://pbs.twimg.com/amplify_video_thumb/1919018179311046656/img/tHbovSEySoZ6vK1U.jpg","type":"video","url":"https://t.co/STy0P38K3N","additional_media_info":{"monetizable":false},"ext_media_availability":{"status":"Available"},"sizes":{"large":{"h":720,"w":1280,"resize":"fit"},"medium":{"h":675,"w":1200,"resize":"fit"},"small":{"h":383,"w":680,"resize":"fit"},"thumb":{"h":150,"w":150,"resize":"crop"}},"original_info":{"height":720,"width":1280,"focus_rects":[]},"allow_download_status":{"allow_download":true},"video_info":{"aspect_ratio":[16,9],"duration_millis":99869,"variants":[{"content_type":"application/x-mpegURL","url":"https://video.twimg.com/amplify_video/1919018179311046656/pl/45EceEo9OywnPZEA.m3u8?tag=16"},{"bitrate":288000,"content_type":"video/mp4","url":"https://video.twimg.com/amplify_video/1919018179311046656/vid/avc1/480x270/QxK-OwgRkiYwh-mt.mp4?tag=16"},{"bitrate":832000,"content_type":"video/mp4","url":"https://video.twimg.com/amplify_video/1919018179311046656/vid/avc1/640x360/Drmw-id5iTdvVgWD.mp4?tag=16"},{"bitrate":2176000,"content_type":"video/mp4","url":"https://video.twimg.com/amplify_video/1919018179311046656/vid/avc1/1280x720/0_GGCY5V89h3gbaB.mp4?tag=16"}]},"media_results":{"result":{"media_key":"13_1919018179311046656"}}}]},"favorited":false,"lang":"zh","possibly_sensitive":false,"possibly_sensitive_editable":true,"retweeted":false,"fact_check":null,"id":"1919020284415512991","view_count":4094,"bookmark_count":15,"created_at":1746365064000,"favorite_count":34,"quote_count":0,"reply_count":15,"retweet_count":2,"user_id_str":"891496559489163264","conversation_id_str":"1919020284415512991","full_text":"上次提到的 ai 翻译硬件\n----\n怎么感觉我介绍产品的时候特别像主播???lol🤣\n----\n整体产品层面不太是技术的创新,更多的是软件交互层的创新,以及硬件的极简化设计,抓得住用户的痛点以及真实的场景。\n----\n总之,这个产品打开了我对 ai 硬件的想象之门,接下来应该会有很多的 ai 硬件的机会,希望大家多给我推推好的产品(ai硬件,DePIN类都可以!)\n----\n大家想要这个吗?\n觉得大概是多少钱呢?","in_reply_to_user_id_str":null,"in_reply_to_status_id_str":null,"is_quote_status":0,"is_ai":null,"ai_score":null},{"bookmarked":false,"display_text_range":[0,159],"entities":{"hashtags":[],"symbols":[],"timestamps":[],"urls":[],"user_mentions":[]},"favorited":false,"lang":"zh","quoted_status_id_str":"1890639062526226574","quoted_status_permalink":{"url":"https://t.co/R0WrtWRQp2","expanded":"https://twitter.com/sanzhichazi1/status/1890639062526226574","display":"x.com/sanzhichazi1/s…"},"retweeted":false,"fact_check":null,"id":"1895376711581344180","view_count":10944,"bookmark_count":20,"created_at":1740727997000,"favorite_count":30,"quote_count":2,"reply_count":7,"retweet_count":2,"user_id_str":"891496559489163264","conversation_id_str":"1895376711581344180","full_text":"🤔 和 crypto 圈子 kol 合作有用吗?\n\n在香港的 Consensus 以及美国 Denver 期间分别和一些项目方做 kol 投放的朋友线下聊了一下,有些说有用,有些说没用。\n\n那有没有用?\n\n会问这个问题的人,大概来自项目方,那回答这个问题前,可能我先会反问三个问题:\n\n1️⃣ 你对于项目想要和 kol 合作的目标和结果是否明确?\n2️⃣ 你的投放策略是什么?\n3️⃣ 你有多少预算?\n\n如果你没有思考过这三个问题的答案,那大概率合作结果和彩票一样,期待中奖吧。\n\n---\n没做好预期目标设计,也就没提前做好预期管理准备。\n———\n\n不同 kol 的属性差别很大,基于需求和目的,需要找不同类别的kol合作。\n\n以下,是我对上面第一个问题的回答 - 项目对于 Kol 需求和目标的分类:\n\n可以分为以下三种\n\n1/ 品牌传播:目的是让大家知道项目\n2/ 社区买量:希望有更多的 Token 购买力\n3/ 产品增长:基于产品使用用户增加和转化\n\n基于需求,我们可以将市场上的 kol 分为:\n\n1. 流量 kol,粉丝基数大,泛赛道,可能和下面的第二种第三种有重叠的\n\n2. 带单 kol,有自己的交易社区,或者跟单用户,自己也会交易。\n\n3. 技术/投研/单赛道kol,这类 kol 一般会输出一些“有价值”的信息,或者对应一些特定的群体,与这类 kol 的合作,可能无法带来具体的买盘,但是对于产品增长可能有一定的帮助,具体需要看类别,假设是交易类的产品,可能还是会第二种有用一些,第三种更适合基础设施类别,或者其他的产品。// 比如说 Defi 赛道和 AI 赛道\n\n-\n\n当然,kol 和项目方的合作,也是双向的,假设是 tokenization 设计不合理的项目,有些大 kol 也不一定会接,原因在于可能觉得赚不到钱\n\n纯赚钱也不一定会接,有时候名声更重要。\n\n-\n\n项目方这边\n\n也还有一些其他的声音,有一些项目方不太喜欢有争议的 kol,他们喊单能力有待考验,但是 fud 能力着实明显,这类 kol 项目方不太愿意合作。\n\n还有一些项目方会因为品牌调性原因,会选择不和一些带有颜色的 kol 合作,怕留下不好印象,但是作为交易类的项目方,应该对这个不是很在意,重点是让更多的用户知道,服务好用户,颜色 kol 的粉丝可能还真是目标用户。\n\n最后,关于 kol 的合作效果,我也具体问了一些人,有几个 kol,是列在我认为适合合作清单,其中有一个比较有意思,被市场认作反指类 kol,但是从项目方反馈来看,是不错的,愿意继续合作系列。\n\n最后,kol 不是万能的。\n\nkol 目前有传播能力和社区构建能力,但没有很好的 GTM 策略,也会一波流就过去了,对项目忠诚度高的 kol 可遇不可求,如何让 kol 随着项目一起成长而获得收益,也是激励策略和空投策略需要考虑的。\n\n最后最后,文化符号,切莫忘了这个。\n\n🩵\n最后,以上为我的观察总结。\n-\n结合数据和 kol Twitter 发布的内容,我还做了一份头部 kol 的表单,下篇公布,为避免遗漏,欢迎关注转发和推荐/自荐好的 kol ❤️\n-","in_reply_to_user_id_str":null,"in_reply_to_status_id_str":null,"is_quote_status":1,"is_ai":null,"ai_score":null},{"bookmarked":false,"display_text_range":[0,185],"entities":{"hashtags":[],"symbols":[],"timestamps":[],"urls":[],"user_mentions":[{"id_str":"1475870679421820931","name":"0xhhh","screen_name":"hhhx402","indices":[38,46]},{"id_str":"1130774555490828288","name":"Haotian | 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饼妹","screen_name":"jinglingcookies","indices":[299,315]},{"id_str":"1460252469745782790","name":"0xJeff","screen_name":"Defi0xJeff","indices":[346,357]},{"id_str":"1572779645828997120","name":"Howe 祛魅 | 𝟎𝐱𝐔💢","screen_name":"0xcryptoHowe","indices":[360,373]}]},"favorited":false,"lang":"zh","retweeted":false,"fact_check":null,"id":"1985023055723458837","view_count":4601,"bookmark_count":22,"created_at":1762101351000,"favorite_count":30,"quote_count":0,"reply_count":7,"retweet_count":5,"user_id_str":"891496559489163264","conversation_id_str":"1985023055723458837","full_text":"想把所有研究 Crypto AI 赛道的博主聚合起来。\n\n我知道的有\n中文\n@hhhx402 老师之前是 ZK 选手,然后算出了 Vitalik 的公式,后面做 AI,vibe coding 也很厉害。\n@tmel0211 老师一直研究这个赛道,也写了很多文章。\n@timotimo007 之前是传统 vc,ai 叙事周期加入,拿了结果,赚了钱了的。\n@alacheng 之前讨论 ai集群的时候聊到了。\n@starzqeth 一直在 virtuals 生态,但也有研究 crypto ai\n@0x_Todd \n@skysyseth 专业是安全+ai,技术很厉害,分享不多,但是技术到位。\n\nEN\n@jinglingcookies 各类ai都有在看,也是 monad 的 ai leader\n@Defi0xJeff 是 @0xcryptoHowe 老师推荐的 en 的 ai researcher\n\n剩下的大家帮我补充一下~","in_reply_to_user_id_str":null,"in_reply_to_status_id_str":null,"is_quote_status":0,"is_ai":null,"ai_score":null},{"bookmarked":false,"display_text_range":[0,170],"entities":{"hashtags":[],"symbols":[{"indices":[143,149],"text":"JELLY"},{"indices":[143,149],"text":"JELLY"}],"timestamps":[],"urls":[{"display_url":"cn.cointelegraph.com/news/hyperliqu…","expanded_url":"https://cn.cointelegraph.com/news/hyperliquid-delists-jelly-perps-citing-suspicious-activity","url":"https://t.co/advz4wlZOT","indices":[10597,10620]},{"display_url":"coindesk.com/markets/2025/0…","expanded_url":"https://www.coindesk.com/markets/2025/03/26/hyperliquid-delists-jellyjelly-after-vault-squeezed-in-usd13m-tussle","url":"https://t.co/0VyDTLXrRL","indices":[10696,10719]},{"display_url":"arringtoncapital.com/blog/hyperliqu…","expanded_url":"https://www.arringtoncapital.com/blog/hyperliquids-tipping-point-three-things-they-must-do-now/#:~:text=Then%2C%20the%20trader%20withdrew%20collateral,confidence%20in%20Hyperliquid%E2%80%99s%20risk%20management","url":"https://t.co/HYjllrQVCv","indices":[10800,10823]},{"display_url":"en.theblockbeats.news/news/57480","expanded_url":"https://en.theblockbeats.news/news/57480","url":"https://t.co/do8uAEOuIN","indices":[10867,10890]},{"display_url":"ainvest.com/news/hyperliqu…","expanded_url":"https://www.ainvest.com/news/hyperliquid-cuts-leverage-limits-4m-loss-eth-liquidation-2503/","url":"https://t.co/BCxDTl5dd8","indices":[10974,10997]}],"user_mentions":[{"id_str":"1527020295059648513","name":"Hyperliquid","screen_name":"HyperliquidX","indices":[81,94]},{"id_str":"1527020295059648513","name":"Hyperliquid","screen_name":"HyperliquidX","indices":[81,94]},{"id_str":"983993370048630785","name":"Arthur 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接连发生两起重大风波:一次是以太坊(ETH)超高杠杆交易引发的剧烈波动与强制平仓事故,另一次是 $JELLY 永续合约疑遭价格操纵并被紧急下架的争议。\n\n这两起事件使社区对该平台的交易机制风险和治理模式产生质疑:一方面,50 倍杠杆的大额头寸清算令平台金库蒙受巨额损失,凸显风险控制漏洞;另一方面,平台在 JELLY 事件中以“验证者投票”之名强行修改价格、平仓赔付,被指有违去中心化精神。\n\nHyperliquid 作为新兴的 DeFi 永续合约平台,本希望以高性能和创新机制迅速崛起,但接连的异常交易动摇了用户信心,也将其高风险杠杆设计与治理透明度问题推上风口浪尖 。\n\n本文将按时间线梳理事件经过,并深入分析其中暴露的机制漏洞与治理争议,探讨 Hyperliquid 未来可能的改进路径和对 DeFi 平台的启示。\n\n2️⃣ 事件时间线\n为理清上述两大事件的发展脉络,下面以时间顺序列出关键节点:\n\n---\n\n3月12日\n一名巨鲸用户利用 Hyperliquid 提供的 50 倍高杠杆建立了名义价值约 2 亿美元的 ETH 多头头寸,并通过提取未实现盈利等操作引发自我强平,成功撤出资金,令平台做市金库 HLP 承担亏损约 400 万美元。该用户据称仍获利约 180 万美元。巨额强平事件使 Hyperliquid 面临严重流动性冲击,社区开始关注平台风险。\n\n3月14日\nHyperliquid 因上述 ETH 大额清算导致 HLP 池损失数百万美元,紧急提高风险参数,包括提高交易者保证金要求和下调杠杆上限。据报道,平台将 BTC 最大杠杆从 50 倍下调至 40 倍,ETH 下调至 25 倍,以增加大额持仓的维持保证金,降低清算冲击。\n\n3月15日\n新的风险控制措施生效,Hyperliquid 要求部分大型持仓维持至少 20% 的保证金比例,以“减少大型头寸在平仓时对市场的系统性冲击”。这被视为平台吸取教训,开始收紧杠杆风险的信号。\n\n3月26日 20:53\n一名交易者在 Hyperliquid 上针对低市值代币 JELLY 建立了价值约 600 万美元的巨额空头仓位,共做空约 4.30 亿枚 JELLY 代币,开仓价格仅 $0.0095。JELLY 为一款 Solana 生态的 meme 代币,流通市值约仅 2500 万美元,流动性极差。\n\n3月26日 21:00-21:15\n该交易者疑似与关联钱包合谋操纵市场:先在去中心化交易所大量抛售 JELLY 现货,短时间内打压外部价格暴跌约 \n 47% 并平掉部分空单获利约 31万 美元,然后立刻从 Hyperliquid 提取了约 276 万美元保证金。此举导致其剩余空头仓(约 3.98 亿 JELLY)保证金不足被强制平仓,由平台清算引擎(HLP金库)以 $0.0113 价格接手了该巨额空头头寸。HLP 金库被动持有大规模 JELLY 空单,埋下巨大风险。\n\n3月26日 21:45\n操纵钱包随即大举在现货市场反向拉高 JELLY 价格,15 分钟 K 线一度拉升超过 100% 后又剧烈波动下跌。受此影响,Hyperliquid 金库持有的空头出现超过 1000 万美元的浮亏。据监测,如果 JELLY 价格继续被推高至约 $0.17(对应市值约 1.5 亿美元),HLP 金库恐面临爆仓,数亿美元资金可能悉数损失。\n\n3月26日 深夜\n面对失控的风险,Hyperliquid 团队/验证者采取了被社区称为“拔网线”的一系列干预措施:紧急下架JELLY永续合约,冻结交易并手动将结算价定为$0.0095(即空头开仓价),强制平掉所有JELLY持仓。这一价位远低于当时去中心化交易所喂价 (~$0.50),有效将攻击者利润清零。官方称此决定经由验证者会议投票通过,以维护市场公平。Hyperliquid 同时宣布,除恶意地址外的所有用户损失将由Hyper Foundation全额赔付,赔付将根据链上数据自动执行。经此“拔线”式结算,平台金库不仅避免了损失,反而因以低价平仓空头实现约70万美元盈利。\n\n3月27日\nJELLY事件引发轩然大波。Hyperliquid 原生代币 HYPE 价格当日下跌约 20% ,众多业内人士在社交媒体质疑平台行为。BitMEX 前 CEO Arthur Hayes @CryptoHayes 直言“别再假装是去中心化”,预测 HYPE 将归零。26 日,中心化交易所迅速行动:Binance @binancezh 和 OKX @okxchinese 宣布上线 JELLY 永续合约,推动 JELLY 现货价格飙涨。有观点认为,这显示出中心化平台在流动性和风控上的优势,以及逐利的敏锐嗅觉。\n\n3月28日\n面对信任危机,Hyperliquid 发布公告称将引入链上验证者投票机制来决定资产下架,以增强治理透明度和去中心化参与 。另一方面,数据显示事件后平台流动性大幅流失:HLP 金库的 TVL 从约 2.4 亿美元骤降至1.95亿美元,短时间内流出近 20% 资金;据 DeFiLlama 统计,平台上的USDC 储备净流出约 1.75 亿美元,持有量从 22.17 亿降至 20.04 亿美元。这表明投资者信心尚未恢复,资金正回流中心化交易所或更安全的领域。\n\n---\n\n3️⃣ 交易机制风险与治理争议\n连环事件背后,Hyperliquid 的交易机制与治理方式暴露出多方面的问题,引发社区热议。\n\n以下将从高杠杆机制漏洞、市场操纵防御不足、去中心化治理 vs. 中心化干预、以及JellyJelly事件决策四个角度分析。\n\n1/ 高杠杆设计的风险漏洞\n\nHyperliquid 以提供高达 50 倍的杠杆交易而吸引用户,但此次 ETH 巨鲸事件证明如此高杠杆+大资金的组合隐藏严重漏洞。首先,高杠杆使得交易者可以用相对少的保证金撬动巨额头寸,价格稍有波动就可能引发强平。而更致命的是,Hyperliquid 此前允许用户提取未实现盈余(unrealized PnL)。这一设计被巨鲸利用:他先用 4.3 百万 USDC 保证金开 50 倍多头拉高ETH价格约 3%(使Hyperliquid 上 ETH 价格明显高于市场价)并获取账面盈利,然后趁市场尚未回落迅速将这部分浮盈提走,导致账户保证金不足被系统强制平仓 。如此一来,巨鲸提前锁定了利润,而平台的清算引擎(HLP金库)被迫接盘高位多头并承担损失。事实证明,该用户通过此策略获利约 180万美金,而平台金库亏损约 400 万美金。\n\n这一“边拉盘边提款”的漏洞在传统中心化交易所早有先例,因风险极高,Binance 等多数交易所禁止交易者提取未结清盈余,要求平仓结算后才能转走资金。Hyperliquid在设计上忽视了这一点,给了攻击者可乘之机。事后不少分析呼吁平台取消未实现盈亏提取功能,强制交易者结清头寸才能兑现盈利,以防再次被恶意利用。\n\n此外,杠杆倍数与头寸规模不应“一刀切”也是本次教训之一。按原先规则,无论仓位大小都可上50倍杠杆,这意味着巨额资金也能以极低保证金进行交易。然而正如知名 DeFi 开发者 Andre Cronje @AndreCronjeTech 所言,在成熟市场中可承受的杠杆倍数应取决于可用流动性和波动性,小额仓位或许能上百倍杠杆,但上亿美金的仓位可能实际只能承受 1.2 倍杠杆风险 。换言之,平台应针对大额持仓动态降低最大杠杆,比固定值更合理。这一点上, Hyperliquid 事后将ETH杠杆上限下调至 25 倍就是亡羊补牢之举。未来还需探索分级杠杆机制,避免再现巨鲸用 50× 杠杆撬动市场的情况。\n\n2/ 平台市场操纵防御能力不足\n\n无论是 ETH 巨鲸自我平仓,还是 JELLY 空头操纵,多发生在流动性薄弱或行情偏离时刻,凸显 Hyperliquid 在防御市场操纵方面的不足。首先,ETH 事件中巨鲸短时间推高平台内 ETH 价差达 3% 以上,原本应该通过资金费率等机制纠正(多头付费给空头以拉平价差),但由于动作太快,资金费率的调节未及时发挥作用。这表明平台风险控制参数(如资金费率调整频率)在极端情况下不够敏捷。\n\n更明显的是 JELLY 事件。攻击者选择了市值低、深度浅的 meme 币下手,充分利用其在中心化交易所以外几乎无人问津的弱点。他们通过在去中心化现货市场(如 Raydium 等)的大额卖单,砸盘造成 JELLY 外部价格暴跌,同时在 Hyperliquid 持有的空头迅速获利并被接管;随后又大举买入拉升价格,使得平台持有的空头头寸产生巨额浮亏。这一连串操作精准打击了 Hyperliquid 的弱点:低流动性币种+统一资金池。由于 Hyperliquid 允许将所有交易对风险共担于同一个做市金库 HLP,攻击者得以用区区几百万撬动数亿美元池子的风险敞口。事实上,短短几十分钟内 JELLY 永续的交易量就超过了该币实际市值总和,这种异常失衡本应触发警报甚至暂停交易。遗憾的是,事发当时平台并未设定此类熔断机制或持仓上限,任由空头头寸规模远超市场容量——直到损失难以承受才被迫“拔线”。\n\n业内人士在事后评论中也指出了 Hyperliquid 在防操纵方面的结构性缺陷。Bitget 交易所 CEO Gracy @GracyBitget批评称,Hyperliquid 的产品设计存在严重缺陷:混合共享的流动性池让所有交易对连坐,一旦某个币出事会殃及整个系统;同时无限制的持仓规模给了操纵者可乘之机。正因为没有总持仓或敞口限制,攻击者才能肆无忌惮地建立数亿规模合约并拉盘砸盘。而 Arrington Capital @Arrington_Cap 的分析也建议,Hyperliquid 应立即下架超低流动性的代币,或至少设定透明的市值与深度门槛,避免上市此类币种带来系统性风险。如果坚持提供此类交易市场,也应考虑隔离不同资产的做市资金池,将高风险资产与主流资产分隔,由自愿的流动性提供者去承担高波动溢价 。这种“隔离舱”设计类似中心化交易所对风险资产采用单独保证金或分账户机制,可以防止小币种风险传导至整个平台。\n\n总之,连续剧般的操纵事件揭示了 Hyperliquid 当前风控体系的薄弱:缺乏异常交易监测和自动干预(如价格偏离检测、持仓/成交量与市值比监控)、资产上架风控不足(无市值深度要求)、以及做市机制过于集中等。这些问题亟需整改,否则平台难以抵御下一个蓄意攻击。\n\n4/ 去中心化治理与中心化干预的冲突\n\n作为号称去中心化的衍生品协议,Hyperliquid 在 JELLY 事件中的处理方式引发了“去中心化治理 vs. 中心化干预”的争议。\n\n在理想的DeFi场景中,协议应由代码规则自动运行,重大决策通过链上治理投票决定,避免人为干预。然而这次Hyperliquid 面对极端风险时选择了人工介入市场:直接修改预言机价格并强制结算合约。尽管官方事后声明此举是“验证者达成共识”后采取的行动,“类似于其他区块链在紧急情况下由验证者协作决定暂停”等等,但在外界看来,这与中心化交易所的“人为控盘”并无二致。正如 BitMEX 前 CEO Arthur Hayes 尖锐指出:“别再假装 Hyperliquid 是去中心化的”,因为当其遇到危机时采取的措施与传统中心化平台别无二致——直接由内部决策改写交易结果。\n\n这样的做法在加密社区引发了信任危机。一些用户质疑 Hyperliquid 所谓的验证者投票是否只是走过场:验证者是谁?投票过程和依据是否透明?为何没有更公开的社区参与?目前来看,Hyperliquid 的验证者主要归属其 Hyper Foundation 基金会(至少此前 JELLY 下架决定是由基金会验证者紧急做出的),这难免给人中心化治理的印象。去中心化倡导者担心,这种先斩后奏的干预破坏了市场公平与透明原则——交易者本应按市场规则结算盈亏,却被团队单方面更改价格平仓(哪怕目的是阻止攻击)。有分析甚至质疑此举在法律上可能存在问题。毕竟,Hyperliquid 合约用户可能会认为平台篡改了合同约定的价格数据。\n\n然而,另一派观点则认为,在当时情形下,若无此果断干预,平台整体可能破产,普通用户资金亦无法保障。从务实角度看,适度的中心化介入挽救了局面。正如 BNB 链在 2022 年遭黑客攻击后由验证者协调回滚交易,保护了链上资产一样(尽管这同样违背了不可篡改性原则),Hyperliquid 此举可以被视作非常时期的非常手段。有论者指出,与其纠结决策是否去中心化,不如关注决策是否正确且有据。在危机下能够迅速拍板、承担责任,本身也是对用户负责的一种表现。\n\n归根结底,这暴露出去中心化衍生品平台面临的两难:完全按链上规则办事,可能导致极端情况下无人能及时止血,进而平台毁灭;临时人为干预,又损及去中心化信誉,让用户心生疑虑。Hyperliquid需要在“代码即法律”与灵活风险应对之间找到平衡。从此次事件看,该平台偏向了后者,但随后也强调会改进治理透明度,以弥补信任缺口。\n\n5/ “JellyJelly 事件”的强制清算与治理决策\n\n以 JELLY 事件为例,我们进一步审视 Hyperliquid 的治理决策过程及其引发的争议。当晚平台选择将 JELLY 永续市场价格冻结在 $0.0095 并强制平仓,这一价格正是攻击者空头的起始价,使其辛苦操纵的利润化为乌有。同时,Hyperliquid 宣布通过 Hyper Foundation 拿出资金赔偿除恶意账户外的所有受影响用户,基本做到用户无辜不受损。从结果上看,攻击者几乎白忙一场反倒小亏,平台金库转危为安还略有盈余。这样的处理方式无疑在效果上保护了大多数用户和协议安全。\n\n但是,在手段上却极具争议:Hyperliquid 相当于单方面重订了合约价格,这在去中心化交易所历史上极为罕见。一些交易员指出,他们的 JELLY 仓位本该按市场价巨亏或大赚,却被平台按一个人为价格结算,盈利的用户收益被抹去,亏损的用户损失由基金会补上。这种“事后人工清算”被批评为开了危险先例:若平台今后都可如此调整价格,那用户如何信任交易结果不会再次被修改?\n\nHyperliquid 声称这一决策经过了验证者治理投票,并非团队独断。确实,Hyperliquid 区块链上的共识节点(验证者)有权限协调紧急事务,这相当于一种链上治理。但问题在于,普通用户对验证者的决策过程几乎一无所知。事发时并未有公开提案和投票公示,一切都是在几个小时内内部完成。直到平台在 X(推特)上公告,大家才知道JELLY合约被移除和平仓价是多少。这种不透明的治理很难令社区信服其公平性。有行业专家呼吁 Hyperliquid 应制定明确定义的应急治理方案,包括在什么条件下可以由验证者介入、如何通知社区以及事后追认等,以提升信任。\n\n值得注意的是,Hyperliquid 正尝试改进治理架构。事件第二天,官方宣布已在部署链上验证者投票功能,今后类似下架决策将通过链上投票表决并公示结果 。甚至在 3 月 29 日对另一个代币 MYRO 进行了链上投票测试。这显示团队意识到了需要更公开的治理流程来挽回声誉。此外,官方也表示将提高系统透明度、改进投票机制的健全性 。这些举措能否真正让社区参与进来、监督决策,还有待观察。\n\n总的来说,JELLY 事件体现了 Hyperliquid 在危机处理中以中心化手段弥补去中心化机制缺陷的典型案例。平心而论,团队迅速止损避免了更大崩盘,展现了执行力;但牺牲了制度信誉,引来了各方对于去中心化和公平性的拷问。这一矛盾也为整个DeFi行业敲响警钟:如何设计既抗操纵又少人工干预的治理与风控,是亟需解决的难题。\n\n4️⃣ 对Hyperliquid未来路径的思考\n\n接连的风波将决定Hyperliquid未来的命运:是吸取教训、改进机制从而东山再起,抑或因信任流失而被市场淘汰。结合业内观点和该团队后续反应,我们对Hyperliquid的未来路径提出以下思考。\n\n机制设计与风控改进\n\n1. 杠杆与保证金机制改革: 首先,Hyperliquid 需要彻底堵住高杠杆漏洞。这包括是否立即取消“不平仓提取浮盈”功能,正如中心化同行所遵循的规则。事实上,Hyperliquid 官方在事件后已降低最大杠杆倍数并提高保证金比例,就是在朝正确方向调整。未来应考虑动态杠杆或阶梯保证金制度:根据持仓规模和市场流动性自动调整可用杠杆。例如,小额交易可给予较高杠杆,大额头寸则强制降低杠杆上限(类似传统期货的逐级保证金制度)。Cronje 等 DeFi 专家也主张去掉固定杠杆倍数概念,引入与市场条件挂钩的风险参数。这将使类似巨鲸操纵的难度大大增加。\n\n2. 持仓限额和总敞口限制: 平台应设定单一资产的持仓上限或总开仓量限制。如 Arrington 资本建议,当某市场未平仓合约总量接近或超过该资产流通市值时,系统应自动限制新开仓或提高保证金,必要时触发熔断 。在JELLY事件中,如果提前限定了 JELLY 市场的最大开仓规模,就不会出现合约成交量远超代币市值的荒谬局面。虽然去中心化平台上难以严格限制单账户持仓(用户可换钱包分散持有),但全局性的 Open Interest 限制是可行且必要的。Hyperliquid 据称也计划降低流动性差币种的全局开仓上限,以防范类似风险。\n\n3. 分离高风险资产池: 当前 Hyperliquid 的 HLP 金库对所有交易对提供做市,在正常情况下提高了资金利用率,但极端情况下导致鸡蛋放在一个篮子里。未来一条出路是引入隔离的做市资金池或保险资金池:将高波动、小市值资产的风险与主流币隔离开。例如设立独立的高风险做市池,允许风险偏好高的 LP 参与,为这些资产提供流动性并获取更高费率,但不影响主池安全。中心化交易所早有类似做法(如 FTX/Binance 对部分山寨合约实行独立保证金模式) ,DeFi 领域也可借鉴。这一改变能降低单一事件对整个平台的冲击。Gracy 也特别指出“混合资金池”是隐患所在,Hyperliquid 必须对此进行重构。\n\n4. 加强异常监控与预警机制: 平台应开发更智能的风险监控:包括链上&链下价格联动监测,当某交易对价格与外部市场出现异常偏离时及时警示或限制交易;交易量/持仓与市值比监控,出现异常放大时自动冻结或审核;以及梯度强平机制,避免一次性平掉巨额仓位造成瀑布效应。此外,建立保险基金或引入外部清算人,在极端情况下接管不良资产,也是增强抗风险性的手段。总之,要将本次事件中靠人工判断干预的部分,转化为事先写好的规则与应急预案,尽量减少临场拍脑袋决策的成分。这不仅能提升安全性,也有助于恢复用户对系统稳定按规则运行的信心。\n\n5️⃣ 中心化交易所的竞争压力\n\nHyperliquid 此次受挫,直接受益者似乎是中心化交易所:Binance、OKX 等纷纷趁机争夺 JELLY 交易热度,显示出 CEX 在处理极端行情时更游刃有余。相较之下,Hyperliquid 的品牌形象和资金体量都遭受打击。后续它将面临来自 CEX 的更大竞争压力:\n\n- 用户信任与迁移: 由于“拔网线”事件削弱了信任,不少用户可能更倾向回到有深厚流动性和声誉的大型交易所。数据已经体现这点:事件后 Hyperliquid 资金迅速流出 。除非平台拿出切实改进,否则这种“用脚投票”还会继续。正如 Bitget CEO 所言,对于任何交易所,信任比资金更重要,一旦丧失将难以挽回。Hyperliquid 必须迅速重建信用,否则有沦为下一个 FTX 的风险。\n\n- 差异化价值主张: 去中心化交易平台相较中心化同行的卖点在于无需信任中介、用户自托管资产、公开透明等。然而此次 Hyperliquid 的操作在一些人看来有失透明、公平,反而像“没有 KYC 的离岸中心化交易所”。这无疑削弱了其差异化优势。未来 Hyperliquid 需要加强宣传和实践其去信任特性,比如全部决策链上记录、资金储备可验证等,以重新凸显与 CEX 的不同。另一方面,它还能提供 CEX 没有的创新功能(例如更快的结算、组合保证金跨链等)来吸引专业用户。但前提是风控可靠,否则创新也只会带来新风险。\n\n- 竞争策略调整: 过去 Hyperliquid 为了迅速拓展用户,采取了上架众多热门币种、提供高杠杆的策略,以与 CEX 抗衡。但正如 Arrington Capital 指出的,这种“拼命给最高杠杆、上最多币”的增长策略在规模变大后难以持续。未来与其正面比拼刺激性,不如在用户体验、费率、社区治理上寻找突破。例如,更低的手续费、更公平透明的规则,或者引入社群自治的激励,打造忠诚用户群体。中心化巨头有资金和规模优势,但 DeFi 平台可利用社区力量和创新速度取胜。Hyperliquid 需要证明,经历风波后它依然有能力提供既安全又高效的交易环境,否则用户会用离开来表达选择。\n\n值得一提的是,本次事件也让行业反思:完全去中心化的永续合约协议是否真的比中心化平台更安全可靠?币安CEO赵长鹏(CZ)在事件后也隐晦地提示过,去中心化交易所若风控不到位,其劣势会显现(他曾提及某些链上项目因不显示强平价且采用ADL而问题频出) 。这提醒我们,DeFi要赢得与CEX的竞争,不仅要理念先进,更要在实际表现上让用户放心。\n\n6️⃣ 去中心化治理的可能出路\n\n风波之后,有观点呼吁 Hyperliquid 应当更加去中心化,让社区参与治理,从根本上避免“小团队暗箱操作”的嫌疑。然而,完全的去中心化在当前阶段未必是万能药。一份分析指出,如果 Hyperliquid 一开始就是完全去中心化的架构,反而可能无法在数小时内做出拯救平台的决定 ——因为真正的全民治理往往决策缓慢,面对瞬息万变的攻击会错失良机。因此,与其一味增加治理参与人数,不如提高治理质量和透明度 。\n\nHyperliquid接下来的去中心化路径或许在于:公开规则,有限授权,透明监督。\n\n具体来说:\n\n- 制定公开的风险参数和处理流程: \n平台应将哪些指标达到什么阈值会触发紧急措施、验证者有何权限、用户资产保障如何等预先写成规则并公示。这样一旦发生异常,社区清楚发生了什么以及将采取什么动作,避免信息不对称引发恐慌。\n\n- 加强验证者去中心化和问责: \n当前Hyperliquid的验证者主要属于官方基金会 。未来应吸纳更多独立节点加入,提高决策多样性。同时,验证者投票记录应上链公开,让社区监督其是否按照既定规则行事,必要时可启用治理投票更换不当验证者。只有当决策过程透明化,用户才能重拾对治理的信任。\n\n- 逐步引入社区治理:\n 在风险可控的范围内,可考虑引入 HYPE 代币持有者的治理投票权。例如非紧急的参数调整、新市场上线/下架,由社区提案投票决定,验证者执行。这一方面实现去中心化参与,另一方面验证者仍可在紧急时刻代社区做出临时决定,但事后需接受社区审议和追责。这种“社区+验证者”双层治理或许是平衡效率与民主的折中方案。\n\n- 拥抱开源与审计: \n去中心化不仅指决策,还包括代码和数据透明。Hyperliquid应尽快开源更多的模块代码,并定期发布审计和风险报告,让社区了解平台运行状况。某种程度上,透明本身就是最好的去信任手段:当用户能亲自验证系统健壮性,才不必完全依赖对团队的主观信任。\n\n总之,Hyperliquid未来的出路并非简单地“更加中心化”或“更加去中心化”,而是在保留高效反应能力的同时,尽可能提高治理透明度和社区参与度。正如一评论所言,关键不在于绝对的中心化或去中心化,而在于达成optimal balance(最优平衡),即既能快速应对风险,又能恪守加密行业核心的公开公平原则。\n\n7️⃣ 结语:教训与展望\n\nHyperliquid 近期的剧烈波动和平仓风波,为所有 DeFi 衍生品平台敲响了警钟。从教训看:一味追求高杠杆和多资产覆盖来快速扩张,容易埋下系统性风险;缺乏完善的风控机制和透明的治理体系,平台难以承受恶意攻击的考验。在短短数月内,Hyperliquid 经历了从明星新秀到信任危机的过山车,这既暴露其自身问题,也提醒整个行业:去中心化交易所若要走向主流,必须在机制设计和治理架构上精益求精。\n\n所幸的是,危机也带来了变革契机。Hyperliquid 已经开始调整杠杆和保证金政策,引入链上投票等治理改进。这些举措如果落实并持续优化,未尝不能帮助其重建信誉。毕竟,平台历史累计盈利尚有结余,技术性能优势依然存在。只要痛定思痛、加强风控,Hyperliquid 仍有机会赢回用户青睐。在更长远的未来,我们期待看到一个更安全、更透明的去中心化衍生品平台生态:在那里,极端行情可以被平稳度过,攻击漏洞被最大限度堵塞,治理决策让社区放心参与。\n\n这不仅是 Hyperliquid 的目标,也是整个 DeFi 永续合约领域努力的方向。\n\n最后,本次事件的经验教训对于所有从业者而言都弥足珍贵。如何在去中心化和安全稳定之间取得平衡,将决定下一代交易协议的成败。Hyperliquid 的故事尚未结束,它的应对之道和演变路径将为行业提供重要参考。正如有人所说,“不要浪费任何一场危机”——期待 Hyperliquid 能够从危机中涅槃,给去中心化金融带来正面示范,同时推动整个行业在治理和机制设计上迈上新台阶 。\n\n参考文献:\n1/ Cointelegraph中文:《Hyperliquid以可疑市场操纵为由紧急下架JELLY永续合约》https://t.co/advz4wlZOT\n2/ CoinDesk:《HyperLiquid Delists JELLY After Vault Squeezed in $13M Tussle》https://t.co/0VyDTLXrRL\n3/ Arrington Capital博客:《Hyperliquid Under Attack: Three Things They Must Do Now》https://t.co/HYjllrQVCv\n4/ Odaily星球日报:《Hyperliquid “拔网线”式强制结算事件全解析》https://t.co/do8uAEOuIN\n5/ AInvest新闻:《Hyperliquid Cuts Leverage Limits After $4M Loss From ETH 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给我们奖金,让想法变成产品。\n♥️","in_reply_to_user_id_str":null,"in_reply_to_status_id_str":null,"is_quote_status":1,"is_ai":null,"ai_score":null},{"bookmarked":false,"display_text_range":[0,159],"entities":{"hashtags":[],"symbols":[],"timestamps":[],"urls":[],"user_mentions":[]},"favorited":false,"lang":"zh","quoted_status_id_str":"1890639062526226574","quoted_status_permalink":{"url":"https://t.co/R0WrtWRQp2","expanded":"https://twitter.com/sanzhichazi1/status/1890639062526226574","display":"x.com/sanzhichazi1/s…"},"retweeted":false,"fact_check":null,"id":"1895376711581344180","view_count":10944,"bookmark_count":20,"created_at":1740727997000,"favorite_count":30,"quote_count":2,"reply_count":7,"retweet_count":2,"user_id_str":"891496559489163264","conversation_id_str":"1895376711581344180","full_text":"🤔 和 crypto 圈子 kol 合作有用吗?\n\n在香港的 Consensus 以及美国 Denver 期间分别和一些项目方做 kol 投放的朋友线下聊了一下,有些说有用,有些说没用。\n\n那有没有用?\n\n会问这个问题的人,大概来自项目方,那回答这个问题前,可能我先会反问三个问题:\n\n1️⃣ 你对于项目想要和 kol 合作的目标和结果是否明确?\n2️⃣ 你的投放策略是什么?\n3️⃣ 你有多少预算?\n\n如果你没有思考过这三个问题的答案,那大概率合作结果和彩票一样,期待中奖吧。\n\n---\n没做好预期目标设计,也就没提前做好预期管理准备。\n———\n\n不同 kol 的属性差别很大,基于需求和目的,需要找不同类别的kol合作。\n\n以下,是我对上面第一个问题的回答 - 项目对于 Kol 需求和目标的分类:\n\n可以分为以下三种\n\n1/ 品牌传播:目的是让大家知道项目\n2/ 社区买量:希望有更多的 Token 购买力\n3/ 产品增长:基于产品使用用户增加和转化\n\n基于需求,我们可以将市场上的 kol 分为:\n\n1. 流量 kol,粉丝基数大,泛赛道,可能和下面的第二种第三种有重叠的\n\n2. 带单 kol,有自己的交易社区,或者跟单用户,自己也会交易。\n\n3. 技术/投研/单赛道kol,这类 kol 一般会输出一些“有价值”的信息,或者对应一些特定的群体,与这类 kol 的合作,可能无法带来具体的买盘,但是对于产品增长可能有一定的帮助,具体需要看类别,假设是交易类的产品,可能还是会第二种有用一些,第三种更适合基础设施类别,或者其他的产品。// 比如说 Defi 赛道和 AI 赛道\n\n-\n\n当然,kol 和项目方的合作,也是双向的,假设是 tokenization 设计不合理的项目,有些大 kol 也不一定会接,原因在于可能觉得赚不到钱\n\n纯赚钱也不一定会接,有时候名声更重要。\n\n-\n\n项目方这边\n\n也还有一些其他的声音,有一些项目方不太喜欢有争议的 kol,他们喊单能力有待考验,但是 fud 能力着实明显,这类 kol 项目方不太愿意合作。\n\n还有一些项目方会因为品牌调性原因,会选择不和一些带有颜色的 kol 合作,怕留下不好印象,但是作为交易类的项目方,应该对这个不是很在意,重点是让更多的用户知道,服务好用户,颜色 kol 的粉丝可能还真是目标用户。\n\n最后,关于 kol 的合作效果,我也具体问了一些人,有几个 kol,是列在我认为适合合作清单,其中有一个比较有意思,被市场认作反指类 kol,但是从项目方反馈来看,是不错的,愿意继续合作系列。\n\n最后,kol 不是万能的。\n\nkol 目前有传播能力和社区构建能力,但没有很好的 GTM 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模型设计合理,开发能力到位,且踩中舆论风口。\n-\n立刻想把我的余额都打给他\n-\n好吧\n留一点吃饭钱 https://t.co/JxoLTw8I1p","in_reply_to_user_id_str":null,"in_reply_to_status_id_str":null,"is_quote_status":0,"is_ai":null,"ai_score":null},{"bookmarked":false,"display_text_range":[0,273],"entities":{"hashtags":[],"symbols":[{"indices":[3074,3081],"text":"XKNOWN"}],"timestamps":[],"urls":[{"display_url":"xKnown.ai","expanded_url":"http://xKnown.ai","url":"https://t.co/zmgDEaB8yG","indices":[518,541]},{"display_url":"xKnown.ai","expanded_url":"http://xKnown.ai","url":"https://t.co/zmgDEaB8yG","indices":[1148,1171]},{"display_url":"xKnown.ai","expanded_url":"http://xKnown.ai","url":"https://t.co/zmgDEaB8yG","indices":[1207,1230]},{"display_url":"xKnown.ai","expanded_url":"http://xKnown.ai","url":"https://t.co/zmgDEaB8yG","indices":[1705,1728]},{"display_url":"xKnown.ai","expanded_url":"http://xKnown.ai","url":"https://t.co/zmgDEaB8yG","indices":[2115,2138]},{"display_url":"xKnown.ai","expanded_url":"http://xKnown.ai","url":"https://t.co/zmgDEaB8yG","indices":[2926,2949]},{"display_url":"app.virtuals.io/geneses/5764","expanded_url":"https://app.virtuals.io/geneses/5764","url":"https://t.co/s03o6r6hIp","indices":[3728,3751]}],"user_mentions":[{"id_str":"1932099312026333184","name":"xKnown.ai","screen_name":"xKnownai","indices":[39,48]},{"id_str":"1930979907380920320","name":"0xDeLambert","screen_name":"AWeb3Researcher","indices":[203,219]},{"id_str":"1757751734359764992","name":"Anna","screen_name":"Anna_xeq3","indices":[229,239]},{"id_str":"1932099312026333184","name":"xKnown.ai","screen_name":"xKnownai","indices":[39,48]},{"id_str":"1930979907380920320","name":"0xDeLambert","screen_name":"AWeb3Researcher","indices":[203,219]},{"id_str":"1757751734359764992","name":"Anna","screen_name":"Anna_xeq3","indices":[229,239]},{"id_str":"1429192255277989892","name":"EtherMage","screen_name":"ethermage","indices":[3404,3414]},{"id_str":"1416874867086045192","name":"Vader 🧢","screen_name":"VaderResearch","indices":[3425,3439]},{"id_str":"481756924","name":"shikhai","screen_name":"theshikhai","indices":[3449,3460]}]},"favorited":false,"lang":"en","retweeted":false,"fact_check":null,"id":"1936034143659606431","view_count":2321,"bookmark_count":0,"created_at":1750421484000,"favorite_count":8,"quote_count":4,"reply_count":3,"retweet_count":3,"user_id_str":"891496559489163264","conversation_id_str":"1936034143659606431","full_text":"Let me briefly introduce this project: @xKnownai\n\nIt’s launching tonight at 8:00 PM. The project’s co-founder and Chief Scientist holds a PhD in AI + Blockchain from NUS. I’ve spoken with their team Lam @AWeb3Researcher and Anna @Anna_xeq3 - super solid!\n\nLooking at their whitepaper, many might find it difficult to understand because it’s quite complex.\n\nSo let me break it down from three angles: real-world problem solving, application scenarios, and business model.\n\n1. What Problem Does It Solve?\n\nAt its core, https://t.co/zmgDEaB8yG tackles the pricing of voice data.\n\nWhy is this important?\n\nMost voice data today is provided through data labeling platforms and data service providers. However, there’s a lack of authoritative third-party pricing mechanisms. So voice data faces two big challenges:\n\n • Data privacy and confidentiality\n • Quality assessment and valuation\n\nData providers can’t directly send data to buyers — digital information is easy to copy. But the buyer doesn’t know the data content or quality in advance — what if it’s junk data?\n\nCurrently, most data transactions are 1-to-1 and operate like black boxes.\n\n2. https://t.co/zmgDEaB8yG’s Tech Advantage — Yotta Protocol\n\nhttps://t.co/zmgDEaB8yG leverages a technology called Yotta to shift from 1-to-1 to 1-to-many or many-to-many data transactions.\n\nThis allows large companies to purchase user data in bulk, with all transaction info on-chain — yet only the buyer and seller can access the data, ensuring third-party privacy.\n\nThe co-founder authored the academic paper “Yotta: A Novel Large-Scale Trustless Data Trading Scheme for Blockchain System,” which was recently added to the Nanyang Blockchain Association.\n\nhttps://t.co/zmgDEaB8yG positions itself as a voice data valuation agent, providing objective, third-party quality assessments and setting standard pricing benchmarks recognized by the market.\n\nThis also unlocks a new market mechanism:\n\nBefore:\n\nData transactions followed a (C →) B → B model — consumers generated data, but had no way to profit directly. Middlemen (B) captured most of the value.\n\nNow:\n\nWith https://t.co/zmgDEaB8yG, C → B becomes possible — end users can directly sell their own voice data.\n\n3. Hardware Product & First Principles\n\nNow, recording voice data just to sell it can be a hassle — it’s time-consuming and complex for users.\n\nThat’s why their AI smart recorder is key:\nIt can automatically transcribe meetings, consultations, conversations, or lectures, and apply AI-generated summaries and labels. This transforms everyday activity into structured, tradable data — without disrupting user behavior.\n\nThis is how they enable data ownership and data monetization in daily life.\n\nAlso, selling hardware itself is a viable revenue stream.\n\nThe AI voice recorder meets a real-world need, and they’ve already gained both Web2 and Web3 users.\n\n4. Tokenomics\n\nWe also discussed the token model. 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Hardworking & 谦虚 & Open\n\n👀","in_reply_to_user_id_str":null,"in_reply_to_status_id_str":null,"is_quote_status":1,"is_ai":null,"ai_score":null},{"bookmarked":false,"display_text_range":[0,173],"entities":{"hashtags":[],"symbols":[{"indices":[371,375],"text":"TAO"},{"indices":[461,465],"text":"TAO"},{"indices":[737,741],"text":"TAO"},{"indices":[1028,1032],"text":"TAO"},{"indices":[1630,1634],"text":"TAO"},{"indices":[2089,2093],"text":"TAO"},{"indices":[2388,2392],"text":"TAO"}],"timestamps":[],"urls":[],"user_mentions":[{"id_str":"1908276659712864256","name":"Bittensor","screen_name":"bittensor","indices":[81,91]},{"id_str":"1908276659712864256","name":"Bittensor","screen_name":"bittensor","indices":[81,91]}]},"favorited":false,"lang":"zh","quoted_status_id_str":"1985004881305072001","quoted_status_permalink":{"url":"https://t.co/I2N7ABxq8x","expanded":"https://twitter.com/0xBeyondLee/status/1985004881305072001","display":"x.com/0xBeyondLee/st…"},"retweeted":false,"fact_check":null,"id":"1985025579905925264","view_count":1641,"bookmark_count":5,"created_at":1762101952000,"favorite_count":4,"quote_count":0,"reply_count":2,"retweet_count":0,"user_id_str":"891496559489163264","conversation_id_str":"1985025579905925264","full_text":"我不记得是前年还是去年写过一篇研报。\n\n借你这个问题,发出来一下\n一年多前写的“Bittensor 生态系统角色和运作机制”\n\n--\n什么是 Bittensor @bittensor ?\n\nBittensor 是一个无许可的 P2P 网络,利用区块链通证经济激励 AI 产品的生成与运营,促进去中心化、抗审查的 AI 发展。它旨在避免主流 AI 产品被巨头控制和垄断,通过提供开放的生态系统,让更多的参与者能够贡献和受益。\n\n--\n生态参与角色及其关系\n\nBittensor 网络中主要有以下三种角色:\n\n1/ 矿工 (Miners):AI 产品与服务的提供商。除了直接运维 AI 大模型外,还包括 AI 产业链的其他环节,如数据存储和提供用于 AI 训练的数据集和预训练。矿工的竞争力在于以尽可能低的成本提供高质量的产品,从而获得更多的 $TAO 激励。\n2/ 验证者 (Validators):负责评价矿工产品与服务质量的裁判,同时充当传递用户需求和矿工服务的中继节点。成为验证者的门槛是需要质押 $TAO,质押的 $TAO 越多,验证者对最终评价结果的影响力越大。\n3/ 用户 (Users):享用矿工服务的一方,包括终端用户和使用 AI 服务构建应用的开发者。\n\n简单来说,矿工是供给方,用户是需求方,而验证者则是传递需求和服务的中继以及评价服务质量的裁判。\n\n--\nBittensor 的代币经济\n\nBittensor 的代币被称为 $TAO,总供应量为 21,000,000 枚。每个新区块会增发 1 枚 $TAO,每 4 年减半一次。目前,Bittensor 每 12 秒产生一个新区块,每天新增发 7200 枚 $TAO。\n\n新区块奖励的分配\n\n新产出的 $TAO 的分配比例为:\n\n- 41% 分配给验证者 (Validators)\n- 41% 分配给矿工 (Miners)\n- 18% 分配给子网所有者 (Subnet Owners)\n\n具体而言,新区块奖励的分配有两个阶段:\n\nRoot 的验证者对其他子网进行评分:通过 Yuma Consensus 机制得出每条子网能够分配的比例。\n子网内部的奖励分配:每条子网的奖励中,18% 固定分配给该子网的所有者,41% 由该子网上的验证者瓜分,41% 由该子网上的矿工瓜分。具体分配比例由 Yuma Consensus 决定。\n\nYuma 共识机制\n\nYuma 共识是一套计算新产出的 $TAO 如何分配的共识机制,不是 Bittensor 区块链网络的共识机制。具体步骤如下:\n\n汇总评分矩阵 (W):每个验证者会给每个子网评分,形成一个 64*33 的矩阵。\n计算中间值 Trust 和 Rank:依据评分矩阵和质押向量计算中间值 Trust,再计算 Rank。\n得到共识结果 (Consensus):通过 Rank 加权平均得到最终的共识结果。\n计算最终释放比例 (Emission):依据共识结果计算最终的释放比例。\n\n例如,假设 Root 验证者经过共识决定分配 10.6% 给某个子网,该子网的所有者可以获得 10.6%*18%=1.908% 的区块奖励,子网上的验证者和矿工各自瓜分 10.6%*41%=4.346% 的区块奖励。\n\n/ 什么是 Subnets?如何成为 Subnet?目前数据\n\nSubnets 的定义与功能:Bittensor 网络中的 AI 商品实际都发生在 Subnets 上。每条 Subnet 都有专门的用例,例如文本生成、图片生成和价格预测等。\n创建 Subnet 的要求:创建一个新的 Subnet 至少需要锁定 100 枚 $TAO。\n目前的 Subnet 数量:目前 Bittensor 网络中共有 45 个子网。\n\n/ Root 子网\n\nRoot 是 Bittensor 的治理中心,有 64 个验证者,全部来自其余 32 条子网中质押 $TAO 数量最大的前 64 个验证者。Root 没有真正的矿工,其余 32 条子网充当矿工的角色。Root 验证者对其余子网进行评分,通过 Yuma Consensus 得出每条子网的区块奖励比例。\n\nSubnets 的现状\n\n现有的 45 个子网:每条子网的用例各有不同,覆盖了文本生成、图像生成、价格预测等领域。\nEmission 分配:45 个子网中,业务集中在数据整理、文字与图像转化等相对门槛较低的场景,但一些高价值的子网(如 SN18 和 SN21)因其目标和市场契合度高,获得了较高的 Emission 分配。\n创新方向:信息查询、LSTAO 与 Bittensor War、Depin + AI、链上辅助交易工具、链上风险提示工具、Bittensor 终端用户体验优化、链游内容创造等方向具有潜力。\n\nBittensor 生态系统\n\n1. 子网:基于激励的竞争机制\n\n每个子网(Subnet)通过提供特定 AI 服务和产品参与到基于激励的竞争中。矿工在子网上提供 AI 服务,并通过验证者的评价获得 $TAO 激励。\n\n2. 区块链:支持子网运行\n\nBittensor 的区块链支持所有子网的正常运行,使基于激励的竞争市场去中心化、无需许可且抗串通。这意味着区块链记录和管理子网的所有活动和结果,确保系统的公平和透明。\n\n3. 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Hardworking & 谦虚 & Open\n\n👀","in_reply_to_user_id_str":null,"in_reply_to_status_id_str":null,"is_quote_status":1,"is_ai":null,"ai_score":null},{"bookmarked":false,"display_text_range":[0,173],"entities":{"hashtags":[],"symbols":[{"indices":[371,375],"text":"TAO"},{"indices":[461,465],"text":"TAO"},{"indices":[737,741],"text":"TAO"},{"indices":[1028,1032],"text":"TAO"},{"indices":[1630,1634],"text":"TAO"},{"indices":[2089,2093],"text":"TAO"},{"indices":[2388,2392],"text":"TAO"}],"timestamps":[],"urls":[],"user_mentions":[{"id_str":"1908276659712864256","name":"Bittensor","screen_name":"bittensor","indices":[81,91]},{"id_str":"1908276659712864256","name":"Bittensor","screen_name":"bittensor","indices":[81,91]}]},"favorited":false,"lang":"zh","quoted_status_id_str":"1985004881305072001","quoted_status_permalink":{"url":"https://t.co/I2N7ABxq8x","expanded":"https://twitter.com/0xBeyondLee/status/1985004881305072001","display":"x.com/0xBeyondLee/st…"},"retweeted":false,"fact_check":null,"id":"1985025579905925264","view_count":1641,"bookmark_count":5,"created_at":1762101952000,"favorite_count":4,"quote_count":0,"reply_count":2,"retweet_count":0,"user_id_str":"891496559489163264","conversation_id_str":"1985025579905925264","full_text":"我不记得是前年还是去年写过一篇研报。\n\n借你这个问题,发出来一下\n一年多前写的“Bittensor 生态系统角色和运作机制”\n\n--\n什么是 Bittensor @bittensor ?\n\nBittensor 是一个无许可的 P2P 网络,利用区块链通证经济激励 AI 产品的生成与运营,促进去中心化、抗审查的 AI 发展。它旨在避免主流 AI 产品被巨头控制和垄断,通过提供开放的生态系统,让更多的参与者能够贡献和受益。\n\n--\n生态参与角色及其关系\n\nBittensor 网络中主要有以下三种角色:\n\n1/ 矿工 (Miners):AI 产品与服务的提供商。除了直接运维 AI 大模型外,还包括 AI 产业链的其他环节,如数据存储和提供用于 AI 训练的数据集和预训练。矿工的竞争力在于以尽可能低的成本提供高质量的产品,从而获得更多的 $TAO 激励。\n2/ 验证者 (Validators):负责评价矿工产品与服务质量的裁判,同时充当传递用户需求和矿工服务的中继节点。成为验证者的门槛是需要质押 $TAO,质押的 $TAO 越多,验证者对最终评价结果的影响力越大。\n3/ 用户 (Users):享用矿工服务的一方,包括终端用户和使用 AI 服务构建应用的开发者。\n\n简单来说,矿工是供给方,用户是需求方,而验证者则是传递需求和服务的中继以及评价服务质量的裁判。\n\n--\nBittensor 的代币经济\n\nBittensor 的代币被称为 $TAO,总供应量为 21,000,000 枚。每个新区块会增发 1 枚 $TAO,每 4 年减半一次。目前,Bittensor 每 12 秒产生一个新区块,每天新增发 7200 枚 $TAO。\n\n新区块奖励的分配\n\n新产出的 $TAO 的分配比例为:\n\n- 41% 分配给验证者 (Validators)\n- 41% 分配给矿工 (Miners)\n- 18% 分配给子网所有者 (Subnet Owners)\n\n具体而言,新区块奖励的分配有两个阶段:\n\nRoot 的验证者对其他子网进行评分:通过 Yuma Consensus 机制得出每条子网能够分配的比例。\n子网内部的奖励分配:每条子网的奖励中,18% 固定分配给该子网的所有者,41% 由该子网上的验证者瓜分,41% 由该子网上的矿工瓜分。具体分配比例由 Yuma Consensus 决定。\n\nYuma 共识机制\n\nYuma 共识是一套计算新产出的 $TAO 如何分配的共识机制,不是 Bittensor 区块链网络的共识机制。具体步骤如下:\n\n汇总评分矩阵 (W):每个验证者会给每个子网评分,形成一个 64*33 的矩阵。\n计算中间值 Trust 和 Rank:依据评分矩阵和质押向量计算中间值 Trust,再计算 Rank。\n得到共识结果 (Consensus):通过 Rank 加权平均得到最终的共识结果。\n计算最终释放比例 (Emission):依据共识结果计算最终的释放比例。\n\n例如,假设 Root 验证者经过共识决定分配 10.6% 给某个子网,该子网的所有者可以获得 10.6%*18%=1.908% 的区块奖励,子网上的验证者和矿工各自瓜分 10.6%*41%=4.346% 的区块奖励。\n\n/ 什么是 Subnets?如何成为 Subnet?目前数据\n\nSubnets 的定义与功能:Bittensor 网络中的 AI 商品实际都发生在 Subnets 上。每条 Subnet 都有专门的用例,例如文本生成、图片生成和价格预测等。\n创建 Subnet 的要求:创建一个新的 Subnet 至少需要锁定 100 枚 $TAO。\n目前的 Subnet 数量:目前 Bittensor 网络中共有 45 个子网。\n\n/ Root 子网\n\nRoot 是 Bittensor 的治理中心,有 64 个验证者,全部来自其余 32 条子网中质押 $TAO 数量最大的前 64 个验证者。Root 没有真正的矿工,其余 32 条子网充当矿工的角色。Root 验证者对其余子网进行评分,通过 Yuma Consensus 得出每条子网的区块奖励比例。\n\nSubnets 的现状\n\n现有的 45 个子网:每条子网的用例各有不同,覆盖了文本生成、图像生成、价格预测等领域。\nEmission 分配:45 个子网中,业务集中在数据整理、文字与图像转化等相对门槛较低的场景,但一些高价值的子网(如 SN18 和 SN21)因其目标和市场契合度高,获得了较高的 Emission 分配。\n创新方向:信息查询、LSTAO 与 Bittensor War、Depin + AI、链上辅助交易工具、链上风险提示工具、Bittensor 终端用户体验优化、链游内容创造等方向具有潜力。\n\nBittensor 生态系统\n\n1. 子网:基于激励的竞争机制\n\n每个子网(Subnet)通过提供特定 AI 服务和产品参与到基于激励的竞争中。矿工在子网上提供 AI 服务,并通过验证者的评价获得 $TAO 激励。\n\n2. 区块链:支持子网运行\n\nBittensor 的区块链支持所有子网的正常运行,使基于激励的竞争市场去中心化、无需许可且抗串通。这意味着区块链记录和管理子网的所有活动和结果,确保系统的公平和透明。\n\n3. 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Hardworking & 谦虚 & Open\n\n👀","in_reply_to_user_id_str":null,"in_reply_to_status_id_str":null,"is_quote_status":1,"is_ai":null,"ai_score":null},{"bookmarked":false,"display_text_range":[0,173],"entities":{"hashtags":[],"symbols":[{"indices":[371,375],"text":"TAO"},{"indices":[461,465],"text":"TAO"},{"indices":[737,741],"text":"TAO"},{"indices":[1028,1032],"text":"TAO"},{"indices":[1630,1634],"text":"TAO"},{"indices":[2089,2093],"text":"TAO"},{"indices":[2388,2392],"text":"TAO"}],"timestamps":[],"urls":[],"user_mentions":[{"id_str":"1908276659712864256","name":"Bittensor","screen_name":"bittensor","indices":[81,91]},{"id_str":"1908276659712864256","name":"Bittensor","screen_name":"bittensor","indices":[81,91]}]},"favorited":false,"lang":"zh","quoted_status_id_str":"1985004881305072001","quoted_status_permalink":{"url":"https://t.co/I2N7ABxq8x","expanded":"https://twitter.com/0xBeyondLee/status/1985004881305072001","display":"x.com/0xBeyondLee/st…"},"retweeted":false,"fact_check":null,"id":"1985025579905925264","view_count":1641,"bookmark_count":5,"created_at":1762101952000,"favorite_count":4,"quote_count":0,"reply_count":2,"retweet_count":0,"user_id_str":"891496559489163264","conversation_id_str":"1985025579905925264","full_text":"我不记得是前年还是去年写过一篇研报。\n\n借你这个问题,发出来一下\n一年多前写的“Bittensor 生态系统角色和运作机制”\n\n--\n什么是 Bittensor @bittensor ?\n\nBittensor 是一个无许可的 P2P 网络,利用区块链通证经济激励 AI 产品的生成与运营,促进去中心化、抗审查的 AI 发展。它旨在避免主流 AI 产品被巨头控制和垄断,通过提供开放的生态系统,让更多的参与者能够贡献和受益。\n\n--\n生态参与角色及其关系\n\nBittensor 网络中主要有以下三种角色:\n\n1/ 矿工 (Miners):AI 产品与服务的提供商。除了直接运维 AI 大模型外,还包括 AI 产业链的其他环节,如数据存储和提供用于 AI 训练的数据集和预训练。矿工的竞争力在于以尽可能低的成本提供高质量的产品,从而获得更多的 $TAO 激励。\n2/ 验证者 (Validators):负责评价矿工产品与服务质量的裁判,同时充当传递用户需求和矿工服务的中继节点。成为验证者的门槛是需要质押 $TAO,质押的 $TAO 越多,验证者对最终评价结果的影响力越大。\n3/ 用户 (Users):享用矿工服务的一方,包括终端用户和使用 AI 服务构建应用的开发者。\n\n简单来说,矿工是供给方,用户是需求方,而验证者则是传递需求和服务的中继以及评价服务质量的裁判。\n\n--\nBittensor 的代币经济\n\nBittensor 的代币被称为 $TAO,总供应量为 21,000,000 枚。每个新区块会增发 1 枚 $TAO,每 4 年减半一次。目前,Bittensor 每 12 秒产生一个新区块,每天新增发 7200 枚 $TAO。\n\n新区块奖励的分配\n\n新产出的 $TAO 的分配比例为:\n\n- 41% 分配给验证者 (Validators)\n- 41% 分配给矿工 (Miners)\n- 18% 分配给子网所有者 (Subnet Owners)\n\n具体而言,新区块奖励的分配有两个阶段:\n\nRoot 的验证者对其他子网进行评分:通过 Yuma Consensus 机制得出每条子网能够分配的比例。\n子网内部的奖励分配:每条子网的奖励中,18% 固定分配给该子网的所有者,41% 由该子网上的验证者瓜分,41% 由该子网上的矿工瓜分。具体分配比例由 Yuma Consensus 决定。\n\nYuma 共识机制\n\nYuma 共识是一套计算新产出的 $TAO 如何分配的共识机制,不是 Bittensor 区块链网络的共识机制。具体步骤如下:\n\n汇总评分矩阵 (W):每个验证者会给每个子网评分,形成一个 64*33 的矩阵。\n计算中间值 Trust 和 Rank:依据评分矩阵和质押向量计算中间值 Trust,再计算 Rank。\n得到共识结果 (Consensus):通过 Rank 加权平均得到最终的共识结果。\n计算最终释放比例 (Emission):依据共识结果计算最终的释放比例。\n\n例如,假设 Root 验证者经过共识决定分配 10.6% 给某个子网,该子网的所有者可以获得 10.6%*18%=1.908% 的区块奖励,子网上的验证者和矿工各自瓜分 10.6%*41%=4.346% 的区块奖励。\n\n/ 什么是 Subnets?如何成为 Subnet?目前数据\n\nSubnets 的定义与功能:Bittensor 网络中的 AI 商品实际都发生在 Subnets 上。每条 Subnet 都有专门的用例,例如文本生成、图片生成和价格预测等。\n创建 Subnet 的要求:创建一个新的 Subnet 至少需要锁定 100 枚 $TAO。\n目前的 Subnet 数量:目前 Bittensor 网络中共有 45 个子网。\n\n/ Root 子网\n\nRoot 是 Bittensor 的治理中心,有 64 个验证者,全部来自其余 32 条子网中质押 $TAO 数量最大的前 64 个验证者。Root 没有真正的矿工,其余 32 条子网充当矿工的角色。Root 验证者对其余子网进行评分,通过 Yuma Consensus 得出每条子网的区块奖励比例。\n\nSubnets 的现状\n\n现有的 45 个子网:每条子网的用例各有不同,覆盖了文本生成、图像生成、价格预测等领域。\nEmission 分配:45 个子网中,业务集中在数据整理、文字与图像转化等相对门槛较低的场景,但一些高价值的子网(如 SN18 和 SN21)因其目标和市场契合度高,获得了较高的 Emission 分配。\n创新方向:信息查询、LSTAO 与 Bittensor War、Depin + AI、链上辅助交易工具、链上风险提示工具、Bittensor 终端用户体验优化、链游内容创造等方向具有潜力。\n\nBittensor 生态系统\n\n1. 子网:基于激励的竞争机制\n\n每个子网(Subnet)通过提供特定 AI 服务和产品参与到基于激励的竞争中。矿工在子网上提供 AI 服务,并通过验证者的评价获得 $TAO 激励。\n\n2. 区块链:支持子网运行\n\nBittensor 的区块链支持所有子网的正常运行,使基于激励的竞争市场去中心化、无需许可且抗串通。这意味着区块链记录和管理子网的所有活动和结果,确保系统的公平和透明。\n\n3. 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Shota values continuous learning, iteration, and community contribution, trusting that innovation flourishes best when ideas are exchanged freely and improved upon collaboratively.","facts":"Fun fact: Shota once spent three months developing and documenting a geospatial volumetric clouds system implemented in Three.js and R3F, highlighting his dedication to mastering challenging technical feats and sharing them openly.","strength":"His greatest strengths lie in deep technical expertise, relentless dedication to quality, and a natural talent for merging artistic design with engineering precision. He's also adept at communicating complex concepts clearly, which amplifies his influence within niche technical communities.","weakness":"However, his intense focus on perfection and technical complexity can sometimes lead to slower output and may alienate less technically savvy audiences. 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With a background that traverses microbiology to computer engineering, Temi’s journey showcases a relentless pursuit of growth and innovation in the software world. Passionate about building products that make a real impact, Temi’s narrative is as inspiring as their code.","purpose":"To revolutionize the tech landscape by creating innovative products that solve real-world problems and inspire others to break barriers in their own careers.","beliefs":"Temi values continuous learning, resilience, and the power of networking. They believe that career paths are non-linear and that passion, hard work, and connection are essential ingredients for success. 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Additionally, the sheer volume of tweets could dilute focus, making it harder to capture sustained audience attention on key topics.","recommendation":"To grow their audience on X, Temi should lean into their storytelling superpower by sharing more behind-the-scenes stories and lessons learned from both failures and successes. Engaging more with the tech community through thoughtful threads and timely responses can amplify reach and position Temi as a go-to Innovator voice.","roast":"Temi’s so humble about their frontend skills, you’d think they’re moonlighting as a backend ninja—too modest to admit they probably could command the frontend world if they wanted, but hey, superheroes don’t always wear capes or boast about their secret powers.","win":"Landing a senior role at Bloomberg after navigating layoffs at Meta and securing a fully funded Master’s scholarship in Switzerland marks Temi as a tenacious achiever who turns every challenge into a winning opportunity."},"created":1763001242738,"type":"the innovator","id":"_iamtpo"},{"user":{"id":"1888306693362032640","name":"Locally AI - Local AI Chat","description":"Run AI models like Llama, Gemma, and more on your iPhone and iPad. Offline. No login. No data collection. 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Also, he’s been deeply involved with LLMs since the Ada era—a true early adopter!","strength":"Ian’s strengths lie in his versatile expertise across software development, public speaking, community organization, and advocacy. His ability to embrace risk and share honest, sometimes brutally honest, insights sets him apart as a thought leader and innovator.","weakness":"His high-octane style and rapid-fire presence sometimes make it challenging to engage followers who prefer more structured, slow-burn content. The lack of retweets on his posts could hint at an underleveraged network effect or occasional niche appeal.","roast":"Ian’s like a coding Swiss Army knife who’s seen so many battles—you’re not sure if you’re following a tech guru or a cage fighter preparing for the next round. Just try not to crash your startup faster than your tweets get retweeted!","win":"Ian’s biggest win? Building a vibrant personal brand that spans tech innovation, community leadership, and real-world grit—plus snagging medals inside *and* outside the octagon!","recommendation":"To grow Ian’s presence on X, he should engage more actively with his network by retweeting and amplifying relevant voices while threading his deep-dive tech insights with engaging storytelling. Hosting AMAs or live-tweeting events about emerging tech like LLMs could also ignite follower interaction and expand his reach."},"created":1763000476062,"type":"the innovator","id":"ianissoawesome"},{"user":{"id":"1976906537932410880","name":"一川","description":"独立开发者|做个有乐趣的人","followers_count":23,"friends_count":134,"statuses_count":319,"profile_image_url_https":"https://pbs.twimg.com/profile_images/1976910771545317376/LSbuOFH4_normal.jpg","screen_name":"RichieY13785","location":"","entities":{"description":{"urls":[]}}},"details":{"type":"The Innovator","description":"一川 is an independent developer who cherishes fun and meaningful work, blending creativity with practical insights. They engage in technical reflections and share everyday experiences, creating a unique and approachable presence. Their tweets show a blend of thoughtful commentary and personal passions, reflecting a well-rounded and inquisitive mind.","purpose":"To inspire others through innovation and personal authenticity, demonstrating that work and life can be both productive and enjoyable. By sharing technical insights alongside everyday joys, they aim to cultivate a community that values creativity, learning, and genuine engagement.","beliefs":"Values honesty, self-expression, and continuous improvement. Believes that fun is an essential part of meaningful work and that innovation stems from authentic curiosity and passion. Also respects leadership qualities like confidence and individuality, acknowledging the complexity of human potential.","facts":"Fun fact: Although 一川’s follower count isn’t displayed, a single retweet of a podcast about Elon Musk amassed over 280,000 views, indicating moments of impactful reach despite generally modest engagement.","strength":"Independent thinker who brings fresh perspectives and combines technical skills with everyday wisdom. Skilled at offering insightful yet relatable content that appeals to diverse interests, from software to lifestyle. Strong adaptability and ability to connect different domains naturally.","weakness":"Engagement levels fluctuate significantly, with most tweets receiving minimal interaction aside from a viral retweet. May benefit from more consistent audience interaction and clearer focus to build and sustain a loyal follower base.","recommendation":"Leverage the viral potential shown in the Elon Musk retweet by creating original content around innovation, success stories, and personal growth. Engage followers by asking questions and sharing behind-the-scenes development insights to build rapport. 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With a passion for real-world problem-solving, Aimar bridges cutting-edge technology and meaningful global change, cutting through performative noise to connect with genuine founders. His tweets reveal a thoughtful critique of Silicon Valley’s bubble, a dedication to transformative ideas, and a keen eye for emerging AI breakthroughs.","purpose":"To revolutionize how AI and technology are applied globally by fostering authentic innovation that tackles serious, high-impact problems beyond the usual venture capital echo chamber. Aimar aims to inspire and uplift real founders who focus on meaningful changes, particularly in underrepresented regions and fields.","beliefs":"Aimar believes that true ambition is about solving complex, impactful challenges rather than chasing superficial trends. He values authenticity, deep knowledge, and the courage to tackle problems others overlook. He champions inclusivity for diverse innovators globally, believes in the power of meaningful collaboration, and respects intellectual maturity over performative hype.","facts":"Fun fact: Despite having no publicly listed follower count, Aimar's tweets resonate widely, racking up hundreds of thousands of views and generating thoughtful conversations among real founders and AI enthusiasts alike.","strength":"Aimar’s strength lies in his ability to cut through the noise with sharp, insightful commentary that challenges prevailing tech norms. His broad creative generalist perspective allows him to connect ideas across sectors, and his authentic voice attracts a community of serious innovators and ambitious minds.","weakness":"His direct and sometimes blunt communication style might alienate those who don't align with his vision, potentially limiting his network expansion among more mainstream or less ambitious audiences. Additionally, being too focused on critiquing rather than always presenting solutions may limit broader engagement at times.","recommendation":"To grow his audience on X, Aimar should continue sharing authentic, high-value insights but also incorporate more storytelling and behind-the-scenes glimpses of his AI projects to build deeper emotional connections. Engaging in thoughtful threads and collaborating with other influential founders can help broaden reach while maintaining his credibility as an Innovator.","roast":"Aimar’s idea of ‘ambitious’ is so refined, he probably wouldn’t RSVP to a party unless it involved rethinking the entire concept of social gatherings through an AI lens—meanwhile, he’s following 1392 people, probably just trying to find the real innovators amongst the noise!","win":"Aimar’s biggest win is his ability to spark meaningful discourse on ambition and innovation in AI, highlighted by viral tweets that challenge the Silicon Valley mindset and amplify underrepresented global perspectives."},"created":1763000038910,"type":"the innovator","id":"advicebyaimar"},{"user":{"id":"1461059047789146118","name":"Nikita Andriievskyi","description":"Custom AI-automated systems that scale | Built systems for 6–8 fig agencies | Book a free audit call 👇","followers_count":1297,"friends_count":231,"statuses_count":16230,"profile_image_url_https":"https://pbs.twimg.com/profile_images/1680240843234353153/V-GnP_zN_normal.jpg","screen_name":"NAndriievskyi","location":"Free automation audit →","entities":{"description":{"urls":[]},"url":{"urls":[{"display_url":"intellscale.com/audit","expanded_url":"https://intellscale.com/audit","url":"https://t.co/oFj3mTCvh3","indices":[0,23]}]}}},"details":{"type":"The Innovator","description":"Nikita is a systems genius passionate about building custom AI-automated workflows that help agencies scale beyond the usual revenue ceilings. With a deep understanding of operational bottlenecks and automation, they turn chaos into streamlined success. Always armed with data and a no-nonsense approach, Nikita educates and empowers agencies to think bigger and smarter.","purpose":"To revolutionize agency operations by creating scalable, AI-driven systems that eliminate inefficiencies and unlock substantial revenue growth without increasing headcount.","beliefs":"Processes must be standardized and measurable before layering on automation; AI isn't a magical fix but a powerful tool when applied correctly; transparency and data-driven insights are key to sustainable scaling.","facts":"Fun fact: Despite the hype around AI agents, Nikita boldly debunks their value in most cases and advises starting with solid process mapping and automation first before dabbling in AI.","strength":"Exceptional ability to diagnose operational bottlenecks and design bespoke automated systems that significantly boost agency revenue and client retention while reducing manual errors.","weakness":"Can come across as overly critical or dismissive of popular tools and trends, which might alienate followers who are fans of beginner-friendly platforms like Notion or those eager to jump straight to flashy AI solutions.","recommendation":"To grow your audience on X, lean into your educational style by sharing quick, actionable threads that break down complex automation concepts. Engage more with comments to turn critiques into conversations and use video demos to showcase your systems in action—this will build trust and attract agency leaders hungry for practical growth hacks.","roast":"If innovative thinking was an Olympic sport, you'd be gold... but somehow, you still manage to turn a simple tool recommendation into a TED talk-length roast session that scares away the casual ClickUp fans faster than your followers can say 'automation overload.'","win":"Built systems that enabled multiple 7-figure agencies to manage $1M+ monthly ad spend without adding a single extra employee, effectively scaling operations with precision and minimal overhead."},"created":1762999746017,"type":"the innovator","id":"nandriievskyi"},{"user":{"id":"151000885","name":"Mev-Rael","description":"Founder/CEO @athenno_com | Creator https://t.co/WgRPpCPYw0 | Philosopher-Warrior | Business Science | AI | Python | Behavioral Economics | UXR | Jurisprudence | ENTJ","followers_count":1895,"friends_count":7502,"statuses_count":3883,"profile_image_url_https":"https://pbs.twimg.com/profile_images/1604754241486262273/F3aeH8q1_normal.jpg","screen_name":"Mevrael","location":"Your Dad's Garage","entities":{"description":{"urls":[{"display_url":"arkalos.com","expanded_url":"http://arkalos.com","url":"http://arkalos.com","indices":[35,58]}]},"url":{"urls":[{"display_url":"athenno.com","expanded_url":"https://athenno.com","url":"https://athenno.com","indices":[0,23]}]}}},"details":{"type":"The Innovator","description":"Mev-Rael is a forward-thinking founder and creator who thrives at the intersection of AI, data science, and behavioral economics. With a strong ENTJ personality, they are a strategic philosopher-warrior driving breakthroughs in AI frameworks and business growth. Their content champions the future of tech and practical applications that empower data mastery and innovation.","purpose":"To revolutionize how individuals and businesses harness AI, data, and behavioral insights, enabling them to predict market trends, build intelligent solutions, and lead transformation in their industries.","beliefs":"They believe in the unstoppable evolution of technology as a net job creator rather than a destroyer, emphasizing continuous learning, strategic thinking, and pragmatic innovation. They value intellectual rigor, data-driven decision making, and empowering others through accessible tech frameworks.","facts":"Fun fact: Mev-Rael not only talks AI but actively builds a user-friendly AI framework, Arkalos, that simplifies complex data science tasks like ML, LLM training, and AI agent deployment right from your local environment.","strength":"Exceptional vision and technical expertise combined with strategic communication skills enable them to create cutting-edge tools and inspire a tech-savvy community. Their prolific tweeting frequency and engagement show hustle and commitment to thought leadership.","weakness":"Their intense focus on innovation and technical depth sometimes leads to overwhelming detail and complexity that might alienate newcomers or casual followers unfamiliar with deep AI jargon.","roast":"Mev-Rael is so busy building futuristic AI frameworks and philosophizing about Python that sometimes you wonder if they’ve forgotten humans still need coffee breaks and emojis to stay engaged, not just data models and code snippets.","win":"Successfully launched and built anticipation around Arkalos, a revolutionary AI and data analysis framework, showcasing leadership in emerging tech even without a massive follower base yet.","recommendation":"To grow your audience on X, Mev-Rael should focus on simplifying and narrativizing technical content — create bite-sized tutorials, relatable AI use cases, and engage more with followers through polls and Q&A sessions to build stronger community bonds and convert curiosity into followers."},"created":1762999470113,"type":"the innovator","id":"mevrael"},{"user":{"id":"886222094047993856","name":"BIGmetaOneMemeMax⚡️.edge🦭","description":"Focus on Alpha Innovation | \ncontributor @xeetdotai @Artery_Chain @MyriadMarkets @brevis_zk @ValanniaGame","followers_count":1171,"friends_count":2450,"statuses_count":1599,"profile_image_url_https":"https://pbs.twimg.com/profile_images/1979086854197485568/q745q2SK_normal.jpg","screen_name":"BigMetaOne","location":"","entities":{"description":{"urls":[]}}},"details":{"type":"The Innovator","description":"BIGmetaOneMemeMax⚡️.edge🦭 is a dynamic explorer at the intersection of Alpha Innovation and blockchain gaming, always seeking the next big breakthrough and sharing insights within the crypto community. 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Hardworking & 谦虚 & Open\n\n👀","in_reply_to_user_id_str":null,"in_reply_to_status_id_str":null,"is_quote_status":1,"is_ai":null,"ai_score":null},{"bookmarked":false,"display_text_range":[0,173],"entities":{"hashtags":[],"symbols":[{"indices":[371,375],"text":"TAO"},{"indices":[461,465],"text":"TAO"},{"indices":[737,741],"text":"TAO"},{"indices":[1028,1032],"text":"TAO"},{"indices":[1630,1634],"text":"TAO"},{"indices":[2089,2093],"text":"TAO"},{"indices":[2388,2392],"text":"TAO"}],"timestamps":[],"urls":[],"user_mentions":[{"id_str":"1908276659712864256","name":"Bittensor","screen_name":"bittensor","indices":[81,91]},{"id_str":"1908276659712864256","name":"Bittensor","screen_name":"bittensor","indices":[81,91]}]},"favorited":false,"lang":"zh","quoted_status_id_str":"1985004881305072001","quoted_status_permalink":{"url":"https://t.co/I2N7ABxq8x","expanded":"https://twitter.com/0xBeyondLee/status/1985004881305072001","display":"x.com/0xBeyondLee/st…"},"retweeted":false,"fact_check":null,"id":"1985025579905925264","view_count":1641,"bookmark_count":5,"created_at":1762101952000,"favorite_count":4,"quote_count":0,"reply_count":2,"retweet_count":0,"user_id_str":"891496559489163264","conversation_id_str":"1985025579905925264","full_text":"我不记得是前年还是去年写过一篇研报。\n\n借你这个问题,发出来一下\n一年多前写的“Bittensor 生态系统角色和运作机制”\n\n--\n什么是 Bittensor @bittensor ?\n\nBittensor 是一个无许可的 P2P 网络,利用区块链通证经济激励 AI 产品的生成与运营,促进去中心化、抗审查的 AI 发展。它旨在避免主流 AI 产品被巨头控制和垄断,通过提供开放的生态系统,让更多的参与者能够贡献和受益。\n\n--\n生态参与角色及其关系\n\nBittensor 网络中主要有以下三种角色:\n\n1/ 矿工 (Miners):AI 产品与服务的提供商。除了直接运维 AI 大模型外,还包括 AI 产业链的其他环节,如数据存储和提供用于 AI 训练的数据集和预训练。矿工的竞争力在于以尽可能低的成本提供高质量的产品,从而获得更多的 $TAO 激励。\n2/ 验证者 (Validators):负责评价矿工产品与服务质量的裁判,同时充当传递用户需求和矿工服务的中继节点。成为验证者的门槛是需要质押 $TAO,质押的 $TAO 越多,验证者对最终评价结果的影响力越大。\n3/ 用户 (Users):享用矿工服务的一方,包括终端用户和使用 AI 服务构建应用的开发者。\n\n简单来说,矿工是供给方,用户是需求方,而验证者则是传递需求和服务的中继以及评价服务质量的裁判。\n\n--\nBittensor 的代币经济\n\nBittensor 的代币被称为 $TAO,总供应量为 21,000,000 枚。每个新区块会增发 1 枚 $TAO,每 4 年减半一次。目前,Bittensor 每 12 秒产生一个新区块,每天新增发 7200 枚 $TAO。\n\n新区块奖励的分配\n\n新产出的 $TAO 的分配比例为:\n\n- 41% 分配给验证者 (Validators)\n- 41% 分配给矿工 (Miners)\n- 18% 分配给子网所有者 (Subnet Owners)\n\n具体而言,新区块奖励的分配有两个阶段:\n\nRoot 的验证者对其他子网进行评分:通过 Yuma Consensus 机制得出每条子网能够分配的比例。\n子网内部的奖励分配:每条子网的奖励中,18% 固定分配给该子网的所有者,41% 由该子网上的验证者瓜分,41% 由该子网上的矿工瓜分。具体分配比例由 Yuma Consensus 决定。\n\nYuma 共识机制\n\nYuma 共识是一套计算新产出的 $TAO 如何分配的共识机制,不是 Bittensor 区块链网络的共识机制。具体步骤如下:\n\n汇总评分矩阵 (W):每个验证者会给每个子网评分,形成一个 64*33 的矩阵。\n计算中间值 Trust 和 Rank:依据评分矩阵和质押向量计算中间值 Trust,再计算 Rank。\n得到共识结果 (Consensus):通过 Rank 加权平均得到最终的共识结果。\n计算最终释放比例 (Emission):依据共识结果计算最终的释放比例。\n\n例如,假设 Root 验证者经过共识决定分配 10.6% 给某个子网,该子网的所有者可以获得 10.6%*18%=1.908% 的区块奖励,子网上的验证者和矿工各自瓜分 10.6%*41%=4.346% 的区块奖励。\n\n/ 什么是 Subnets?如何成为 Subnet?目前数据\n\nSubnets 的定义与功能:Bittensor 网络中的 AI 商品实际都发生在 Subnets 上。每条 Subnet 都有专门的用例,例如文本生成、图片生成和价格预测等。\n创建 Subnet 的要求:创建一个新的 Subnet 至少需要锁定 100 枚 $TAO。\n目前的 Subnet 数量:目前 Bittensor 网络中共有 45 个子网。\n\n/ Root 子网\n\nRoot 是 Bittensor 的治理中心,有 64 个验证者,全部来自其余 32 条子网中质押 $TAO 数量最大的前 64 个验证者。Root 没有真正的矿工,其余 32 条子网充当矿工的角色。Root 验证者对其余子网进行评分,通过 Yuma Consensus 得出每条子网的区块奖励比例。\n\nSubnets 的现状\n\n现有的 45 个子网:每条子网的用例各有不同,覆盖了文本生成、图像生成、价格预测等领域。\nEmission 分配:45 个子网中,业务集中在数据整理、文字与图像转化等相对门槛较低的场景,但一些高价值的子网(如 SN18 和 SN21)因其目标和市场契合度高,获得了较高的 Emission 分配。\n创新方向:信息查询、LSTAO 与 Bittensor War、Depin + AI、链上辅助交易工具、链上风险提示工具、Bittensor 终端用户体验优化、链游内容创造等方向具有潜力。\n\nBittensor 生态系统\n\n1. 子网:基于激励的竞争机制\n\n每个子网(Subnet)通过提供特定 AI 服务和产品参与到基于激励的竞争中。矿工在子网上提供 AI 服务,并通过验证者的评价获得 $TAO 激励。\n\n2. 区块链:支持子网运行\n\nBittensor 的区块链支持所有子网的正常运行,使基于激励的竞争市场去中心化、无需许可且抗串通。这意味着区块链记录和管理子网的所有活动和结果,确保系统的公平和透明。\n\n3. 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共识机制。\n\n//\n本研报已经过时,仅供娱乐。","in_reply_to_user_id_str":null,"in_reply_to_status_id_str":null,"is_quote_status":1,"is_ai":null,"ai_score":null},{"bookmarked":false,"display_text_range":[9,32],"entities":{"hashtags":[],"symbols":[],"timestamps":[],"urls":[{"display_url":"t.me/nofx_dev_commu…","expanded_url":"https://t.me/nofx_dev_community/16622","url":"https://t.co/B7nzj6Vw8H","indices":[9,32]}],"user_mentions":[{"id_str":"1983962738532741120","name":"NoFx","screen_name":"nofx_ai","indices":[0,8]}]},"favorited":false,"in_reply_to_screen_name":"nofx_ai","lang":"qme","possibly_sensitive":false,"possibly_sensitive_editable":true,"retweeted":false,"fact_check":null,"id":"1984906788664492464","view_count":19,"bookmark_count":0,"created_at":1762073630000,"favorite_count":0,"quote_count":0,"reply_count":0,"retweet_count":0,"user_id_str":"891496559489163264","conversation_id_str":"1984892660944158978","full_text":"@nofx_ai 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Hardworking & 谦虚 & Open\n\n👀","in_reply_to_user_id_str":null,"in_reply_to_status_id_str":null,"is_quote_status":1,"is_ai":null,"ai_score":null},{"bookmarked":false,"display_text_range":[0,173],"entities":{"hashtags":[],"symbols":[{"indices":[371,375],"text":"TAO"},{"indices":[461,465],"text":"TAO"},{"indices":[737,741],"text":"TAO"},{"indices":[1028,1032],"text":"TAO"},{"indices":[1630,1634],"text":"TAO"},{"indices":[2089,2093],"text":"TAO"},{"indices":[2388,2392],"text":"TAO"}],"timestamps":[],"urls":[],"user_mentions":[{"id_str":"1908276659712864256","name":"Bittensor","screen_name":"bittensor","indices":[81,91]},{"id_str":"1908276659712864256","name":"Bittensor","screen_name":"bittensor","indices":[81,91]}]},"favorited":false,"lang":"zh","quoted_status_id_str":"1985004881305072001","quoted_status_permalink":{"url":"https://t.co/I2N7ABxq8x","expanded":"https://twitter.com/0xBeyondLee/status/1985004881305072001","display":"x.com/0xBeyondLee/st…"},"retweeted":false,"fact_check":null,"id":"1985025579905925264","view_count":1641,"bookmark_count":5,"created_at":1762101952000,"favorite_count":4,"quote_count":0,"reply_count":2,"retweet_count":0,"user_id_str":"891496559489163264","conversation_id_str":"1985025579905925264","full_text":"我不记得是前年还是去年写过一篇研报。\n\n借你这个问题,发出来一下\n一年多前写的“Bittensor 生态系统角色和运作机制”\n\n--\n什么是 Bittensor @bittensor ?\n\nBittensor 是一个无许可的 P2P 网络,利用区块链通证经济激励 AI 产品的生成与运营,促进去中心化、抗审查的 AI 发展。它旨在避免主流 AI 产品被巨头控制和垄断,通过提供开放的生态系统,让更多的参与者能够贡献和受益。\n\n--\n生态参与角色及其关系\n\nBittensor 网络中主要有以下三种角色:\n\n1/ 矿工 (Miners):AI 产品与服务的提供商。除了直接运维 AI 大模型外,还包括 AI 产业链的其他环节,如数据存储和提供用于 AI 训练的数据集和预训练。矿工的竞争力在于以尽可能低的成本提供高质量的产品,从而获得更多的 $TAO 激励。\n2/ 验证者 (Validators):负责评价矿工产品与服务质量的裁判,同时充当传递用户需求和矿工服务的中继节点。成为验证者的门槛是需要质押 $TAO,质押的 $TAO 越多,验证者对最终评价结果的影响力越大。\n3/ 用户 (Users):享用矿工服务的一方,包括终端用户和使用 AI 服务构建应用的开发者。\n\n简单来说,矿工是供给方,用户是需求方,而验证者则是传递需求和服务的中继以及评价服务质量的裁判。\n\n--\nBittensor 的代币经济\n\nBittensor 的代币被称为 $TAO,总供应量为 21,000,000 枚。每个新区块会增发 1 枚 $TAO,每 4 年减半一次。目前,Bittensor 每 12 秒产生一个新区块,每天新增发 7200 枚 $TAO。\n\n新区块奖励的分配\n\n新产出的 $TAO 的分配比例为:\n\n- 41% 分配给验证者 (Validators)\n- 41% 分配给矿工 (Miners)\n- 18% 分配给子网所有者 (Subnet Owners)\n\n具体而言,新区块奖励的分配有两个阶段:\n\nRoot 的验证者对其他子网进行评分:通过 Yuma Consensus 机制得出每条子网能够分配的比例。\n子网内部的奖励分配:每条子网的奖励中,18% 固定分配给该子网的所有者,41% 由该子网上的验证者瓜分,41% 由该子网上的矿工瓜分。具体分配比例由 Yuma Consensus 决定。\n\nYuma 共识机制\n\nYuma 共识是一套计算新产出的 $TAO 如何分配的共识机制,不是 Bittensor 区块链网络的共识机制。具体步骤如下:\n\n汇总评分矩阵 (W):每个验证者会给每个子网评分,形成一个 64*33 的矩阵。\n计算中间值 Trust 和 Rank:依据评分矩阵和质押向量计算中间值 Trust,再计算 Rank。\n得到共识结果 (Consensus):通过 Rank 加权平均得到最终的共识结果。\n计算最终释放比例 (Emission):依据共识结果计算最终的释放比例。\n\n例如,假设 Root 验证者经过共识决定分配 10.6% 给某个子网,该子网的所有者可以获得 10.6%*18%=1.908% 的区块奖励,子网上的验证者和矿工各自瓜分 10.6%*41%=4.346% 的区块奖励。\n\n/ 什么是 Subnets?如何成为 Subnet?目前数据\n\nSubnets 的定义与功能:Bittensor 网络中的 AI 商品实际都发生在 Subnets 上。每条 Subnet 都有专门的用例,例如文本生成、图片生成和价格预测等。\n创建 Subnet 的要求:创建一个新的 Subnet 至少需要锁定 100 枚 $TAO。\n目前的 Subnet 数量:目前 Bittensor 网络中共有 45 个子网。\n\n/ Root 子网\n\nRoot 是 Bittensor 的治理中心,有 64 个验证者,全部来自其余 32 条子网中质押 $TAO 数量最大的前 64 个验证者。Root 没有真正的矿工,其余 32 条子网充当矿工的角色。Root 验证者对其余子网进行评分,通过 Yuma Consensus 得出每条子网的区块奖励比例。\n\nSubnets 的现状\n\n现有的 45 个子网:每条子网的用例各有不同,覆盖了文本生成、图像生成、价格预测等领域。\nEmission 分配:45 个子网中,业务集中在数据整理、文字与图像转化等相对门槛较低的场景,但一些高价值的子网(如 SN18 和 SN21)因其目标和市场契合度高,获得了较高的 Emission 分配。\n创新方向:信息查询、LSTAO 与 Bittensor War、Depin + AI、链上辅助交易工具、链上风险提示工具、Bittensor 终端用户体验优化、链游内容创造等方向具有潜力。\n\nBittensor 生态系统\n\n1. 子网:基于激励的竞争机制\n\n每个子网(Subnet)通过提供特定 AI 服务和产品参与到基于激励的竞争中。矿工在子网上提供 AI 服务,并通过验证者的评价获得 $TAO 激励。\n\n2. 区块链:支持子网运行\n\nBittensor 的区块链支持所有子网的正常运行,使基于激励的竞争市场去中心化、无需许可且抗串通。这意味着区块链记录和管理子网的所有活动和结果,确保系统的公平和透明。\n\n3. 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Hardworking & 谦虚 & Open\n\n👀","in_reply_to_user_id_str":null,"in_reply_to_status_id_str":null,"is_quote_status":1,"is_ai":null,"ai_score":null},{"bookmarked":false,"display_text_range":[0,173],"entities":{"hashtags":[],"symbols":[{"indices":[371,375],"text":"TAO"},{"indices":[461,465],"text":"TAO"},{"indices":[737,741],"text":"TAO"},{"indices":[1028,1032],"text":"TAO"},{"indices":[1630,1634],"text":"TAO"},{"indices":[2089,2093],"text":"TAO"},{"indices":[2388,2392],"text":"TAO"}],"timestamps":[],"urls":[],"user_mentions":[{"id_str":"1908276659712864256","name":"Bittensor","screen_name":"bittensor","indices":[81,91]},{"id_str":"1908276659712864256","name":"Bittensor","screen_name":"bittensor","indices":[81,91]}]},"favorited":false,"lang":"zh","quoted_status_id_str":"1985004881305072001","quoted_status_permalink":{"url":"https://t.co/I2N7ABxq8x","expanded":"https://twitter.com/0xBeyondLee/status/1985004881305072001","display":"x.com/0xBeyondLee/st…"},"retweeted":false,"fact_check":null,"id":"1985025579905925264","view_count":1641,"bookmark_count":5,"created_at":1762101952000,"favorite_count":4,"quote_count":0,"reply_count":2,"retweet_count":0,"user_id_str":"891496559489163264","conversation_id_str":"1985025579905925264","full_text":"我不记得是前年还是去年写过一篇研报。\n\n借你这个问题,发出来一下\n一年多前写的“Bittensor 生态系统角色和运作机制”\n\n--\n什么是 Bittensor @bittensor ?\n\nBittensor 是一个无许可的 P2P 网络,利用区块链通证经济激励 AI 产品的生成与运营,促进去中心化、抗审查的 AI 发展。它旨在避免主流 AI 产品被巨头控制和垄断,通过提供开放的生态系统,让更多的参与者能够贡献和受益。\n\n--\n生态参与角色及其关系\n\nBittensor 网络中主要有以下三种角色:\n\n1/ 矿工 (Miners):AI 产品与服务的提供商。除了直接运维 AI 大模型外,还包括 AI 产业链的其他环节,如数据存储和提供用于 AI 训练的数据集和预训练。矿工的竞争力在于以尽可能低的成本提供高质量的产品,从而获得更多的 $TAO 激励。\n2/ 验证者 (Validators):负责评价矿工产品与服务质量的裁判,同时充当传递用户需求和矿工服务的中继节点。成为验证者的门槛是需要质押 $TAO,质押的 $TAO 越多,验证者对最终评价结果的影响力越大。\n3/ 用户 (Users):享用矿工服务的一方,包括终端用户和使用 AI 服务构建应用的开发者。\n\n简单来说,矿工是供给方,用户是需求方,而验证者则是传递需求和服务的中继以及评价服务质量的裁判。\n\n--\nBittensor 的代币经济\n\nBittensor 的代币被称为 $TAO,总供应量为 21,000,000 枚。每个新区块会增发 1 枚 $TAO,每 4 年减半一次。目前,Bittensor 每 12 秒产生一个新区块,每天新增发 7200 枚 $TAO。\n\n新区块奖励的分配\n\n新产出的 $TAO 的分配比例为:\n\n- 41% 分配给验证者 (Validators)\n- 41% 分配给矿工 (Miners)\n- 18% 分配给子网所有者 (Subnet Owners)\n\n具体而言,新区块奖励的分配有两个阶段:\n\nRoot 的验证者对其他子网进行评分:通过 Yuma Consensus 机制得出每条子网能够分配的比例。\n子网内部的奖励分配:每条子网的奖励中,18% 固定分配给该子网的所有者,41% 由该子网上的验证者瓜分,41% 由该子网上的矿工瓜分。具体分配比例由 Yuma Consensus 决定。\n\nYuma 共识机制\n\nYuma 共识是一套计算新产出的 $TAO 如何分配的共识机制,不是 Bittensor 区块链网络的共识机制。具体步骤如下:\n\n汇总评分矩阵 (W):每个验证者会给每个子网评分,形成一个 64*33 的矩阵。\n计算中间值 Trust 和 Rank:依据评分矩阵和质押向量计算中间值 Trust,再计算 Rank。\n得到共识结果 (Consensus):通过 Rank 加权平均得到最终的共识结果。\n计算最终释放比例 (Emission):依据共识结果计算最终的释放比例。\n\n例如,假设 Root 验证者经过共识决定分配 10.6% 给某个子网,该子网的所有者可以获得 10.6%*18%=1.908% 的区块奖励,子网上的验证者和矿工各自瓜分 10.6%*41%=4.346% 的区块奖励。\n\n/ 什么是 Subnets?如何成为 Subnet?目前数据\n\nSubnets 的定义与功能:Bittensor 网络中的 AI 商品实际都发生在 Subnets 上。每条 Subnet 都有专门的用例,例如文本生成、图片生成和价格预测等。\n创建 Subnet 的要求:创建一个新的 Subnet 至少需要锁定 100 枚 $TAO。\n目前的 Subnet 数量:目前 Bittensor 网络中共有 45 个子网。\n\n/ Root 子网\n\nRoot 是 Bittensor 的治理中心,有 64 个验证者,全部来自其余 32 条子网中质押 $TAO 数量最大的前 64 个验证者。Root 没有真正的矿工,其余 32 条子网充当矿工的角色。Root 验证者对其余子网进行评分,通过 Yuma Consensus 得出每条子网的区块奖励比例。\n\nSubnets 的现状\n\n现有的 45 个子网:每条子网的用例各有不同,覆盖了文本生成、图像生成、价格预测等领域。\nEmission 分配:45 个子网中,业务集中在数据整理、文字与图像转化等相对门槛较低的场景,但一些高价值的子网(如 SN18 和 SN21)因其目标和市场契合度高,获得了较高的 Emission 分配。\n创新方向:信息查询、LSTAO 与 Bittensor War、Depin + AI、链上辅助交易工具、链上风险提示工具、Bittensor 终端用户体验优化、链游内容创造等方向具有潜力。\n\nBittensor 生态系统\n\n1. 子网:基于激励的竞争机制\n\n每个子网(Subnet)通过提供特定 AI 服务和产品参与到基于激励的竞争中。矿工在子网上提供 AI 服务,并通过验证者的评价获得 $TAO 激励。\n\n2. 区块链:支持子网运行\n\nBittensor 的区块链支持所有子网的正常运行,使基于激励的竞争市场去中心化、无需许可且抗串通。这意味着区块链记录和管理子网的所有活动和结果,确保系统的公平和透明。\n\n3. 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Hardworking & 谦虚 & Open\n\n👀","in_reply_to_user_id_str":null,"in_reply_to_status_id_str":null,"is_quote_status":1,"is_ai":null,"ai_score":null},{"bookmarked":false,"display_text_range":[0,173],"entities":{"hashtags":[],"symbols":[{"indices":[371,375],"text":"TAO"},{"indices":[461,465],"text":"TAO"},{"indices":[737,741],"text":"TAO"},{"indices":[1028,1032],"text":"TAO"},{"indices":[1630,1634],"text":"TAO"},{"indices":[2089,2093],"text":"TAO"},{"indices":[2388,2392],"text":"TAO"}],"timestamps":[],"urls":[],"user_mentions":[{"id_str":"1908276659712864256","name":"Bittensor","screen_name":"bittensor","indices":[81,91]},{"id_str":"1908276659712864256","name":"Bittensor","screen_name":"bittensor","indices":[81,91]}]},"favorited":false,"lang":"zh","quoted_status_id_str":"1985004881305072001","quoted_status_permalink":{"url":"https://t.co/I2N7ABxq8x","expanded":"https://twitter.com/0xBeyondLee/status/1985004881305072001","display":"x.com/0xBeyondLee/st…"},"retweeted":false,"fact_check":null,"id":"1985025579905925264","view_count":1641,"bookmark_count":5,"created_at":1762101952000,"favorite_count":4,"quote_count":0,"reply_count":2,"retweet_count":0,"user_id_str":"891496559489163264","conversation_id_str":"1985025579905925264","full_text":"我不记得是前年还是去年写过一篇研报。\n\n借你这个问题,发出来一下\n一年多前写的“Bittensor 生态系统角色和运作机制”\n\n--\n什么是 Bittensor @bittensor ?\n\nBittensor 是一个无许可的 P2P 网络,利用区块链通证经济激励 AI 产品的生成与运营,促进去中心化、抗审查的 AI 发展。它旨在避免主流 AI 产品被巨头控制和垄断,通过提供开放的生态系统,让更多的参与者能够贡献和受益。\n\n--\n生态参与角色及其关系\n\nBittensor 网络中主要有以下三种角色:\n\n1/ 矿工 (Miners):AI 产品与服务的提供商。除了直接运维 AI 大模型外,还包括 AI 产业链的其他环节,如数据存储和提供用于 AI 训练的数据集和预训练。矿工的竞争力在于以尽可能低的成本提供高质量的产品,从而获得更多的 $TAO 激励。\n2/ 验证者 (Validators):负责评价矿工产品与服务质量的裁判,同时充当传递用户需求和矿工服务的中继节点。成为验证者的门槛是需要质押 $TAO,质押的 $TAO 越多,验证者对最终评价结果的影响力越大。\n3/ 用户 (Users):享用矿工服务的一方,包括终端用户和使用 AI 服务构建应用的开发者。\n\n简单来说,矿工是供给方,用户是需求方,而验证者则是传递需求和服务的中继以及评价服务质量的裁判。\n\n--\nBittensor 的代币经济\n\nBittensor 的代币被称为 $TAO,总供应量为 21,000,000 枚。每个新区块会增发 1 枚 $TAO,每 4 年减半一次。目前,Bittensor 每 12 秒产生一个新区块,每天新增发 7200 枚 $TAO。\n\n新区块奖励的分配\n\n新产出的 $TAO 的分配比例为:\n\n- 41% 分配给验证者 (Validators)\n- 41% 分配给矿工 (Miners)\n- 18% 分配给子网所有者 (Subnet Owners)\n\n具体而言,新区块奖励的分配有两个阶段:\n\nRoot 的验证者对其他子网进行评分:通过 Yuma Consensus 机制得出每条子网能够分配的比例。\n子网内部的奖励分配:每条子网的奖励中,18% 固定分配给该子网的所有者,41% 由该子网上的验证者瓜分,41% 由该子网上的矿工瓜分。具体分配比例由 Yuma Consensus 决定。\n\nYuma 共识机制\n\nYuma 共识是一套计算新产出的 $TAO 如何分配的共识机制,不是 Bittensor 区块链网络的共识机制。具体步骤如下:\n\n汇总评分矩阵 (W):每个验证者会给每个子网评分,形成一个 64*33 的矩阵。\n计算中间值 Trust 和 Rank:依据评分矩阵和质押向量计算中间值 Trust,再计算 Rank。\n得到共识结果 (Consensus):通过 Rank 加权平均得到最终的共识结果。\n计算最终释放比例 (Emission):依据共识结果计算最终的释放比例。\n\n例如,假设 Root 验证者经过共识决定分配 10.6% 给某个子网,该子网的所有者可以获得 10.6%*18%=1.908% 的区块奖励,子网上的验证者和矿工各自瓜分 10.6%*41%=4.346% 的区块奖励。\n\n/ 什么是 Subnets?如何成为 Subnet?目前数据\n\nSubnets 的定义与功能:Bittensor 网络中的 AI 商品实际都发生在 Subnets 上。每条 Subnet 都有专门的用例,例如文本生成、图片生成和价格预测等。\n创建 Subnet 的要求:创建一个新的 Subnet 至少需要锁定 100 枚 $TAO。\n目前的 Subnet 数量:目前 Bittensor 网络中共有 45 个子网。\n\n/ Root 子网\n\nRoot 是 Bittensor 的治理中心,有 64 个验证者,全部来自其余 32 条子网中质押 $TAO 数量最大的前 64 个验证者。Root 没有真正的矿工,其余 32 条子网充当矿工的角色。Root 验证者对其余子网进行评分,通过 Yuma Consensus 得出每条子网的区块奖励比例。\n\nSubnets 的现状\n\n现有的 45 个子网:每条子网的用例各有不同,覆盖了文本生成、图像生成、价格预测等领域。\nEmission 分配:45 个子网中,业务集中在数据整理、文字与图像转化等相对门槛较低的场景,但一些高价值的子网(如 SN18 和 SN21)因其目标和市场契合度高,获得了较高的 Emission 分配。\n创新方向:信息查询、LSTAO 与 Bittensor War、Depin + AI、链上辅助交易工具、链上风险提示工具、Bittensor 终端用户体验优化、链游内容创造等方向具有潜力。\n\nBittensor 生态系统\n\n1. 子网:基于激励的竞争机制\n\n每个子网(Subnet)通过提供特定 AI 服务和产品参与到基于激励的竞争中。矿工在子网上提供 AI 服务,并通过验证者的评价获得 $TAO 激励。\n\n2. 区块链:支持子网运行\n\nBittensor 的区块链支持所有子网的正常运行,使基于激励的竞争市场去中心化、无需许可且抗串通。这意味着区块链记录和管理子网的所有活动和结果,确保系统的公平和透明。\n\n3. 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