Channel
@chigua10086
On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry
5,900subscribers
-10 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
| Telegram ID | -1001366249355 |
|---|---|
| Type | Channel |
| Username | @chigua10086 |
| Created | Between 1 April 2018 and 31 July 2021— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 13 August 2026 |
| Measurements held | 4 |
| Confirmed unchanged | 1 time, most recently 13 August 2026 |
| On Telegram | t.me/chigua10086 |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 13 Aug 2026, 13:16 | 5,900 | -1 |
| 10 Aug 2026, 19:18 | 5,901 | -9 |
| 7 Aug 2026, 10:30 | 5,910 | no change |
| 7 Aug 2026, 10:26 | 5,910 | first reading |
44 posts held, back to 2 August 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 9 pagesof Telegram’s post history, 20 posts per page.
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. It is computed over the 8 of 44 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 12 August 2026 |
|---|---|
| Posts held | 44 (2 August 2026 – 12 August 2026) |
| Views total | 10,674 |
| Reactions total | 8 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 12 Aug 2026, 03:44 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.
8 reactions across 4 posts, in 2 distinct kinds. The most used accounts for 75.0% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 6 | 75.0% | |
| 🖕 | 2 | 25.0% |
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 8 of the 44 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 8reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 44 most recent posts we hold, published 2 August 2026 to 12 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.
美国政府想要禁止美国公民使用中国AI模型 却被宪法束缚了手脚 如果联邦政府试图禁止美国公民使用在中国开发的人工智能模型，使用者可能会以侵犯美国宪法第一修正案所赋予的“接收信息权”（通常被称为“听众权利”，listeners' rights）为由，诉请法院宣布该禁令无效。在涉及“听众权利”的判例中，发言者本身是否拥有第一修正案保障的言论自由并不重要；冷战时期的“拉蒙特诉邮政局长案”中，美国联邦最高法院便裁定，一项限制美国人接收外国共产党宣传品权利的法律违宪。 阻断中国模型进入美国的难度尤为突出，因为其中大多数属于开放权重模型。这意味着美国用户可以免费下载模型权重，并将其部署在自己的服务器上。因此，用户可能会提出两项独立的宪法第一修正案主张：一是他们有权通过中国聊天机器人接收信息，二是他们有权下载这些模型的权重。美国政府可以限制美国公民与中国开发者之间的交易，但法律问题十分复杂。 —— 华尔街日报 · 观点
传蜜雪冰城代工星巴克物料，双方回应传闻 8 月 12 日有报道称，前山姆中国 CMO 张青加入博裕资本，操刀星巴克中国供应链改革，纸杯、吸管、抹茶粉等物料将由蜜雪冰城代工。蜜雪冰城客服回应称尚不能确定，将登记反馈核实；星巴克中国表示对市场传闻和猜测不作评论，各项业务正常运行。 新浪财经
美国数据中心新建禁令7月激增 142个城市爆发反对活动 美国政界正在加速踩下数据中心扩建的刹车，最新数据显示，七月美国各地禁止新建数据中心的数量激增至500多个，而6月下旬仅为约300个。这一数据由The Information通过法律文件和新闻报道分析得出，显示出美国地方政府对新建数据中心越来越谨慎的态度，且并未表现出党派之争。这可能对美国AI公司所需的算力扩张构成严重阻碍。 报告显示，共和党和民主党执政的州、城镇和县都已经开始阻止新的数据中心项目，其中，共和党代表的得克萨斯州和民主党代表的纽约州是反抗最突出的两个地区。而促成两党难得统一的关键原因在于，数据中心已经引发美国社会的普遍不满。 —— 财联社
苹果研发照片来源验证技术，帮助确认图片是否由 iPhone 拍摄 苹果正在开发一种用于验证照片来源的新技术，旨在证明一张图片是否真实由 iPhone 相机拍摄。该功能可能通过相机硬件、系统签名和加密认证机制生成可验证信息，以帮助用户识别经过 AI 生成或篡改的图像。随着生成式 AI 让伪造照片越来越容易，苹果希望通过设备级认证提高照片真实性。不过，该技术目前仍处于研发阶段，具体发布时间和实现方式尚未公布。 9To5Mac
Anthropic宣布Claude在证明黎曼猜想过程中取得重大突破 Anthropic重磅发文，让内部研究版Claude去证明「黎曼猜想」，结果失败了。但Claude却在这一世纪难题取得了重大突破——它成功将符合猜想的黎曼Zeta函数零点比例下限，从41.6%一口气拔高到了67.2%。这一成果，在过去37年里，所有人类数学家才推进了0.8%。 如今，Claude直接迈出了一大步，提升了25.6%。Claude结合近期结果和Bombieri在2000年的相关观察，把Weil公式限制在一个有限维的Gabor函数空间中，将解析数论问题表示成一个Hermitian矩阵问题。 —— 36氪
苹果测试长鑫芯片 拟用于销华iPhone设备 美国苹果公司据报在智能手机iPhone与手提电脑MacBook等产品中，测试中国芯片制造商巨擘长鑫存储的记忆体芯片，并计划在部分向中国市场销售的设备中采用。《华尔街日报》9日披露该消息。分析指若是次合作成事，对中国芯片产业意义重大。在人工智能（AI）热潮导致芯片供应短缺的背景下，苹果若能从中国制造商处确保稳定供应，也有助苹果缓解成本压力。 除苹果公司外，消息还披露，手提电脑生产商惠普与Acer为解决记忆体芯片供应紧张问题，也开始在美国以外市场销售的设备中，使用长鑫存储的芯片。知情人士称，惠普与Acer目前仅拥有数量非常有限的存储芯片，两间生产商都寻求为明年生产锁定更多芯片供应。
中国企业与大学研发经费超美跃居首位 在企业和大学的研发费用总额方面，中国已超过美国，位居全球第一。日本文科省报告显示，中国2024年的研发经费为97.1万亿日元，同比增长13.1%，超过了美国（95.3万亿日元）。中国在科研论文数量上于2017年超过美国，跃居全球第一。被公认为研究质量高的前10%高被引论文数量也在2018年跃居首位，而被认为更加优秀的前1%顶尖论文数量自2019年起同样位居第一。 此次中国又在研发经费总额上超过美国，名副其实地走在世界科学研究的最前列。推动中国研发经费增长的是企业投资。比上年增长13％，达75.4万亿日元，在企业研发经费总额上超过美国。其中，计算机、电子和光学产品制造业领域的制造业出现激增。 —— 日经新闻
中国人形机器人制造商占全球出货量逾97% 最新行业数据显示，2026年上半年，中国人形机器人制造商占全球出货量的97%以上，显示中国在这一新兴领域已领先美国。 Smart Analytics Global的数据显示，2026年上半年，全球人形机器人出货量大约 1万9100台，是去年同期5100台的三倍多。这家总部位于美国加利福尼亚州的研究机构预计，今年全球人形机器人出货量将增至约六万台，到2030年将达到50万台。 总部位于上海的智元机器人超越总部位于杭州的宇树科技，跃居市场份额榜首。今年上半年，智元机器人出货量达8400台，占全球出货量的44%，宇树科技则为5900台。 —— 联合早报、彭博社
研究：iPhone 18 Pro生产成本骤增近四成 TrendForce周一发布的最新产业研究称，比较近两代iPhone Pro系列（256GB机型）的BOM成本（原材料、零部件、工具和人工等标准成本），2026年三季度发售的iPhone 18 Pro将较去年同型号新机高出38%。随着存储继续涨价，明年上半年的差距还将进一步扩大。其中，推动iPhone制造成本快速上涨的核心因素依然是存储芯片。 TrendForce拆解称，去年三季度时，手机处理器 (AP) 、面板和存储分别占整体BOM成本的11%、16%和10%。到今年三季度，单单存储一项就占到整体成本的34%，明年上半年还有可能提高至42%，彻底取代以往由处理器和面板主导手机定价的局面。 —— 财联社、TrendForce
长征7号甲运载火箭在发射中解体 中国航天科技集团有限公司北京时间2026年8月10日星期一在海南文昌航天发射中心20:02按计划发射一枚搭载未知载荷的长征7号甲运载火箭。在点火发射后约40秒左右，火箭一级在上升段发生非计划快速解体。事故似乎发生在“最大动压点”（Max-Q）附近，即火箭结构承受应力最大的时刻。目前事故原因尚不清楚。截止目前，中国国家航天局和中国航天科工集团并未发布按照往常惯例在发射后进行任务状态更新。 —— NasaSpaceFlight
宇树科技中一签或能赚20万 8月9日，A股“人形机器人第一股”宇树科技8月10日将在科创板正式开启申购。考虑到宇树科技本次发行流通盘规模较小，又叠加“第一股”的题材光环，多家券商综合测算显示，其预计中签率在万分之二至万分之三之间，远低于长鑫科技0.47%的中签率水平。数据显示，2026年以来A股新股上市首日平均涨幅高达276.04%，若以此测算，中一签宇树科技账面盈利有望突破20万元；若对标年内科创板新股首日466.61%的平均涨幅，单签盈利可达35.18万元。
摩尔线程拟赴港上市，上半年营收增 147% AI 芯片公司摩尔线程宣布计划在港上市，称此举旨在深化国际化战略并吸引研发与管理人才。公司同日披露，上半年营收同比大增 147% 至 17.4 亿元，净亏损从去年同期的 2.709 亿元收窄至 1160 万元。 摩尔线程去年年底在上交所上市，融资 80 亿元，首日股价飙升 425%，自上市以来累计涨幅已超 420%。由前英伟达高管张建中于 2020 年创立，公司最初面向游戏及图形渲染芯片市场，后转向 AI 加速器，与寒武纪、华为共同竞争英伟达退出后留下的市场空白。今年香港 IPO 市场持续火热，年内募资额已超 420 亿美元，创六年新高。 Bloomberg
Showing the 12 most recent of 44 posts we hold for @chigua10086. 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.
Citation-graph rank — 663,147 of 1,480,688entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
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.
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 13 August 2026 — this entry's latest reading, not the date you are reading this.
“时事 | 科技 新闻投稿 中文” (@chigua10086), 5,900 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/chigua10086.
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.