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Channel

泛出海快讯站

@fanchuhai

On this record: Topic · Growth · Engagement · Reactions · Posts · Citations · Cite this entry

7,787subscribers

+1,738 since we began measuring on 26 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1003795382330
TypeChannel
Username@fanchuhai
CreatedBetween 1 February 2026 and 31 July 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded26 August 2026
Last confirmed live19 September 2026
Measurements held7
Confirmed unchanged1 time, most recently 19 September 2026
On Telegramt.me/fanchuhai

Topic

Technology — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 12 September 2026 and assigned it the closest of 31 fixed categories, at 92% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.

Growth

5,5467,7876,666.526 August 2026 — 6,049 subscribers27 August 2026 — 6,051 subscribers2 September 2026 — 6,056 subscribers7 September 2026 — 6,063 subscribers11 September 2026 — 5,974 subscribers14 September 2026 — 5,546 subscribers19 September 2026 — 7,787 subscribers26 August 202619 September 2026
7 measurements spanning 24 days, net +1,738. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 5,210–8,123 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
19 Sept 2026, 17:557,787+2,241
14 Sept 2026, 23:405,546-428
11 Sept 2026, 14:175,974-89
7 Sept 2026, 07:406,063+7
2 Sept 2026, 15:346,056+5
27 Aug 2026, 11:366,051+2
26 Aug 2026, 18:476,049first reading

Engagement

20 posts held, back to 8 August 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 page of Telegram’s post history, 20 posts per page.

ERR · 30 days
9.07%
avg views ÷ 7,787 subscribers
Avg views / post
707
6 posts measured
Reaction rate
19.6%
reactions ÷ views · ER floor
Posts in window
6
of 20 held

ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.

ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.

What these figures were computed from
WindowRolling 30 days · latest post in window 26 August 2026
Posts held20 (8 August 202626 August 2026)
Views total4,239
Reactions total832
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken26 Aug 2026, 18:47 UTC

Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.

Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.

Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.

Reaction mix

2,666 reactions across 20 posts, in 8 distinct kinds. The most used accounts for 20.3% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
54020.3%
🎉52519.7%
🔥51719.4%
👍51019.1%
😁49618.6%
👏291.09%
🥰271.01%
🤩220.825%

No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.

Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.

Coverage. Reactions were read on 20 of the 20 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 2,666 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 20 most recent posts we hold, published 8 August 2026 to 26 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.

Recent posts

26 Aug 2026, 17:20 UTC692 views151 reactionsread 26 August 2026

WhatsApp 通行密钥(Passkeys)用户量突破 10 亿:支持跨系统多密钥绑定,同步上线未知来电识别 【即时通讯与数字安全】 WhatsApp 官方正式发布公告,平台使用通行密钥(Passkeys)登录的活跃用户数已成功突破 10 亿大关。作为生物识别与去密码化(Passwordless)认证普及的重要里程碑,WhatsApp 进一步优化了跨平台安全登录体验,并在 Android 客户端同步推出了针对非联系人来电的智能背景识别功能。 通行密钥(Passkeys)功能升级与配置路径 1、多设备与跨平台兼容 通行密钥允许用户直接通过设备原生的指纹、面容 ID(Face ID)或锁屏密码完成安全身份验证与登录。针对同时跨 Android 与 iOS 设备使用的用户,WhatsApp 现已支持在单一账户中添加并绑定多个通行密钥,消除跨系统换机与重新验证的障碍。 2、官方配置路径 用户可通过访问 WhatsApp 客户端:

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25 Aug 2026, 17:31 UTC696 views152 reactionsread 26 August 2026

任天堂再次对 Switch 模拟器采取毁灭性打击:一天内提交 7 份 DMCA 申请,下架 GitHub 上逾 400 个相关代码库 【知识产权与游戏版权风控】 据科技媒体 Android Authority 报道,任天堂(Nintendo)对其知识产权及硬件保护措施的维权行动再次升级。任天堂在单日内向代码托管平台 GitHub 连续提交了 7 份《数字千年版权法》(DMCA)下架通告,一举清理了超过 400 个与 Nintendo Switch 模拟器相关的开源代码仓库,标志着其对模拟器开发生态的全面封堵。 执法行动与受影响项目 1、打击规模与范围 本次维权行动针对 GitHub 平台上的 Switch 模拟器分支及其二次开发版本(Forks)进行了全网清理,受影响的项目包括 Suyu、Skyline 等知名模拟器的核心仓库及衍生项目。 2、维权法理依据 任天堂在 DMCA 申诉中明确指出,Switch 模拟器通过非法绕

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24 Aug 2026, 17:25 UTC694 views134 reactionsread 26 August 2026

谷歌开源大模型 Gemma 家族下载量突破 10 亿次:衍生变体超 10 万个,构建“Gemmaverse”端侧生态 【人工智能与开源生态】 谷歌公司(Google)正式宣布,由旗下 AI 实验室 Google DeepMind 推出的开源端侧大模型 Gemma 家族全球累计下载量已成功突破 10 亿次。自发布以来,全球开发者依托 Gemma 底座衍生出超过 10 万个定制化模型变体,标志着以 Gemma 为核心的“Gemmaverse”开源开发者生态已具备规模化行业影响力。 生态规模与垂直应用落地 1、规模化开发者生态 Gemma 凭其轻量化、高效率与端侧部署优势,成功吸引全球开源社区参与。10 万余个衍生变体的涌现,推动了 Gemma 从单一开源模型向跨平台、多场景的大模型开源生态(Gemmaverse)跨越。 2多领域垂直产业赋能 谷歌官方列举了 Gemma 在多个前沿及垂直领域的商业化与科研落地案例: 极端与边缘环

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23 Aug 2026, 17:00 UTC686 views132 reactionsread 26 August 2026

AliExpress 被曝光静默运行 WebAudio 指纹跟踪:干扰多点蓝牙设备 【网络安全与技术隐私通报】 据科技媒体 Solidot(奇客)报道,近期有独立开发者发现,阿里巴巴旗下跨境电商平台 AliExpress(速卖通)在用户浏览器后台静默运行高度混淆的安全监控脚本。该脚本通过创建 WebAudio 音频图(WebAudio Fingerprinting)收集设备指纹,并在运行过程中意外占用了系统的音频输出通道,导致支持多点连接(Multipoint)的蓝牙耳机发生音频路由异常。 事件现象与技术原理分析 1、多点蓝牙音频异常联动 多点蓝牙耳机(可同时连接 PC 与手机)的默认逻辑为:PC 端优先输出音频;仅当 PC 无音频信号流时,耳机才自动切换并播放手机端音频。开发者发现,在 Chrome 或 Firefox 浏览器中打开 AliExpress 页面后,即使页面未播放任何声音,手机端音频也会立即中断;关闭该页面后

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22 Aug 2026, 16:45 UTC683 views127 reactionsread 26 August 2026

全国首批“算力词元贷”在广州落地:数据资产化身授信凭证,轻资产企业最高可获 3000 万元融资 【金融创新与数字经济动态】 据央视财经与第一财经报道,全国首批“算力词元贷”金融创新产品在广州正式落地。该产品突破了传统信贷高度依赖房产、厂房等固定资产抵押的风控模式,将人工智能(AI)大模型企业的词元(Token)消耗数据、算力合约及服务供给价值转化为授信依据,为轻资产科创企业开辟了全新的数据资产融资路径。 授信逻辑变革与产品体系 1、风控评估维度的重大创新 不同于传统企业贷款聚焦于实体资产积累,“算力词元贷”将企业历史词元结算数据、词元供给与消耗动态、以及算力合约潜在价值作为核心审核指标,精准匹配 AI 研发与算力密集型企业的实际经营特征。 2、三类矩阵与要素标准 中国银行广州分行针对不同产业链环节,推出了三大细分子产品: 供给贷:面向算力基础设施与 Token 供给侧企业; 应用贷:面向垂直大模型开发与 Token 高频消耗

27👍23🔥21🎉17👏16🥰13🤩7😁3

21 Aug 2026, 16:59 UTC788 views136 reactionsread 26 August 2026

宇树科技成功登陆资本市场首日暴涨:创下中国机器人产业里程碑 【资本市场与硬科技动态】 据路透社及凤凰网科技等多家权威媒体报道,全球领先的人形及四足机器人制造企业宇树科技(Unitree Robotics)正式在上海证券交易所挂牌上市。上市首日,公司股价大幅飙升超过 400%(逾四倍),成为中国机器人产业发展史上的标志性事件,凸显出资本市场对具身智能(Embodied AI)及硬科技赛道的高度认可。 核心资本数据与股权结构 1、公开募集与估值表现 宇树科技本次 IPO 共公开发行约 10% 的股份,顺利募集资金约 9 亿美元。挂牌首日股价飙升逾 400%,标志着本土机器人产业链在资本赋能下迈入全新规模化阶段。 2、创始人股权与企业掌控 现年 36 岁的宇树科技创始人兼 CEO 王兴兴仍持有公司约 20%(五分之一)的股份。伴随首日股价大涨,其个人账面财富已突破 110 亿美元。 行业竞争格局与战略意义 1、全球具身智能赛道

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20 Aug 2026, 17:05 UTC904 views150 reactionsread 26 August 2026

蚂蚁国际推出 Falcon 2.0 时序模型:花旗、汇丰等六家全球顶尖银行接入外汇 AI 预测生态 【金融科技与全球财资管理】 蚂蚁国际(Ant International)正式发布其自主研发的 Falcon 时序模型 2.0(Falcon Time-Series Model 2.0),并宣布与花旗银行(Citi)、汇丰银行(HSBC)、德意志银行(Deutsche Bank)、渣打银行(Standard Chartered)及巴克莱银行(Barclays)等六家全球大型跨国银行达成深度合作。该模型专注于企业级现金流预测与外汇(FX)需求管理,标志着生成式与预测式 AI 在全球银行业核心流动性管理领域的商业化落地。 商业降本效应 1、高精度预测与流动性优化 Falcon 2.0 模型针对多币种、跨时区的复杂交易数据进行实时时序分析,准确预测企业在未来特定时间窗口内的现金流走向与外汇对冲需求,协助银行动态调整流动性头寸,避免资

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19 Aug 2026, 16:46 UTC838 views86 reactionsread 26 August 2026

Telegram 拟申请 .gram 专属顶级域名:推进全员 Web3 域名与 AI 智能建站生态 【Web3 与数字域名生态】 即时通讯巨头 Telegram 创始人帕维尔·杜罗夫(Pavel Durov)通过其官方频道宣布,Telegram 平台已正式向互联网名称与数字地址分配机构(ICANN)提交通用顶级域名(gTLD) .gram 的申请。若该申请获批,Telegram 生态内的十亿级用户将直接获得对应用户名(Username)的专属二级域名分配权,标志着 Telegram 在通信社交与 Web3 基础设施融合上迈出关键一步。 生态价值规划 1、去中心化身份(DID)与域名自动化映射 用户体系打通:成功引入 .gram 后,Telegram 用户无需复杂的 DNS 配置,其平台用户名即可自动映射为开放互联网可访问的二级域名(如 @username 对应 username.gram)。 去中心化资产联动:该体系预计将与

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18 Aug 2026, 17:33 UTC808 views146 reactionsread 26 August 2026

Hurricane Electric (AS6939) 与 Cloudflare (AS13335) 断开对等互联:全球网络可达性引发关注 【网络基础设施与 BGP 路由动态】 据 bgp.tools 及 PeeringDB 等网络测量与 BGP 监控平台最新实时数据,全球知名 IP Transit 网络服务商 Hurricane Electric(HE,AS6939) 与全球最大 Content Delivery Network/DDoS 防御服务商 Cloudflare(AS13335) 已正式断开双方直接的免费对等互联(Direct Peering / Settlement-Free Peering)。截至目前,双方均未发布官方回应或维护公告,此现象究竟源于临时性网络配置故障,抑或是商业对等结算协议(Peering Agreement)纠纷,尚待官方进一步澄清。 影响评估 1、对等互联(Peering)的商业与技术机制

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17 Aug 2026, 19:18 UTC895 views135 reactionsread 26 August 2026

德国反垄断监管裁定苹果修改 ATT 隐私弹窗:消除第三方 App 差别待遇并接受七年监督 【全球反垄断与数据合规】 德国联邦卡特尔局于近日作出监管裁定,认定苹果公司在 iOS 系统中推行的“应用跟踪透明度”框架构成反竞争行为。监管机构指出,苹果对自身第一方应用适用更为宽松的数据采集规则,同时对第三方开发者设置具有引导性与劝退性质的弹窗界面。为合规履责,苹果已承诺在四个月内修改 EU 区域内的 ATT 弹窗设计,并接受为期七年的合规监督。 核心争议 1、自我优待与竞争扭曲 监管机构认定,苹果利用操作系统垄断地位,在“保护用户隐私”的旗号下实施双重标准:自身广告业务可直接利用内部生态数据进行精准推荐,而第三方应用则须经过严苛的弹窗许可,实质上压制了第三方数字广告生态的竞争能力。 2、界面设计强制矫正 裁定要求苹果移除 ATT 弹窗中带有情绪引导、警告倾向的强硬措辞及暗示性图标,确保第三方 App 在申请数据跟踪许可时获得与苹果

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16 Aug 2026, 16:27 UTC720 views87 reactionsread 26 August 2026

摩根大通因监管风险切断 Polymarket 核心银行业务:去中心化预测平台面临合规性考验 【金融合规与 Web3 动态】 依据《金融时报》(Financial Times)等权威媒体报道,华尔街投行巨头摩根大通(JPMorgan Chase)已于此前以“监管合规风险”为由,正式终止了为全球最大去中心化预测市场平台 Polymarket 提供的主力银行账户服务,并要求其迁移至其他金融机构。此举凸显了传统传统金融机构在应对高频事件预测、博彩属性争议及合规审查压力时的极高风险厌恶策略。 监管博弈 1、监管审查升级与“去银行化” 尽管 Polymarket 在收购持牌交易所(QCX)并获得美国商品期货交易委员会(CFTC)框架下的合规路径后重新切入美国市场,但其涉及政治选举押注、体育赛事衍生品及市场操纵疑虑,仍引发了 CFTC 及美国多个州执法部门的持续审查。摩根大通为规避反洗钱(AML)及次级合规风险,选择主动关闭其核心运营账户

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15 Aug 2026, 16:13 UTC583 views34 reactionsread 26 August 2026

特朗普政府解除 TikTok 联邦设备禁令:架构重组完成与风险合规性评估 【监管政策与科技动态】 美国白宫管理和预算办公室(OMB)日前正式发布备忘录,宣布撤销 2023 年颁布的联邦设备 TikTok 使用禁令。这一决策标志着 TikTok 美国业务在完成本土化股权重组与技术架构隔离后,已正式通过美国政府的国家安全评估与法规审核。 重组架构 1、美资控股与治理结构:重组后的 TikTok 美国业务由甲骨文(Oracle)、银湖资本(Silver Lake)等美国本土投资机构组成的大股东联合体主导运营(持股比例超 80%),原始母公司仅保留无操作控制权的少数股权。 2、云端托管与算法独立:美国用户的隐私数据及底层云服务均托管于甲骨文(Oracle)在美国境内的安全云基础设施中;推荐算法与内容审查机制已完成本土化重训与独立审计。 行业影响 1、合规风险出清:白宫禁令的解除,标志着 TikTok 在美商业运营的最大政策悬疾与

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Showing the 12 most recent of 20 posts we hold for @fanchuhai. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.

Mentions

Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.

Named by

Channels on the register whose posts name this channel's handle.

Names

Channels on the register whose handles appear in this channel's posts.

A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.

Cite this entry

A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 19 September 2026 — this entry's latest reading, not the date you are reading this.

“泛出海快讯站” (@fanchuhai), 7,787 subscribers as measured 19 September 2026. Telegram Register, tgregister.com/channel/fanchuhai.

Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.