Telegram RegisterThe public register of Telegram

Channel

AI一线|ShareCentre

@ShareCentre

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

15,511subscribers

+35 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1001421716094
TypeChannel
Username@ShareCentre
Description每日更新最新最全AI新闻 免费节点请关注 @ShareCentrePro 💁‍♂️投放广告请联系 @AS24400
Created25 October 2020measured — cross-checked against a third-party dataset (TGDataset)
First recorded6 August 2026
Last confirmed live12 August 2026
Measurements held7
Confirmed unchanged2 times, most recently 12 August 2026
On Telegramt.me/ShareCentre

Growth

15,47615,51115,493.56 August 2026 — 15,476 subscribers6 August 2026 — 15,476 subscribers7 August 2026 — 15,485 subscribers8 August 2026 — 15,495 subscribers9 August 2026 — 15,499 subscribers10 August 2026 — 15,504 subscribers11 August 2026 — 15,511 subscribers6 August 202611 August 2026
7 measurements spanning 5 days, net +35. 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 15,471–15,516 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
11 Aug 2026, 19:5115,511+7
10 Aug 2026, 17:2615,504+5
9 Aug 2026, 16:0215,499+4
8 Aug 2026, 18:2815,495+10
7 Aug 2026, 15:5415,485+9
6 Aug 2026, 20:3015,476no change
6 Aug 2026, 20:2915,476first reading

Engagement

38 posts held, back to 1 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 17 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
5.22%
avg views ÷ 15,511 subscribers
Avg views / post
810
38 posts measured
Reaction rate
0.148%
reactions ÷ views · ER floor
Posts in window
38
of 38 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. It is computed over the 11 of 38 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 12 August 2026
Posts held38 (1 August 202612 August 2026)
Views total30,793
Reactions total14
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken13 Aug 2026, 01:20 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.

What this channel posts

Photos
1,010
Videos
208
Links
1,100

Lifetime counters from Telegram’s own channel header, read 13 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.

Video runtime
10s
Average length
10s

Measured directly from 1 video with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no mark.

Reaction mix

14 reactions across 8 posts, in 3 distinct kinds. The most used accounts for 50.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
750.0%
🐳535.7%
👍214.3%

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 11 of the 38 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 14reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 38 most recent posts we hold, published 1 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.

Recent posts

12 Aug 2026, 13:00 UTC111 viewsread 13 August 2026
Photo

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12 Aug 2026, 05:44 UTC483 viewsread 13 August 2026
Photo

AI 协作刷新 Grothendieck 常数上下界,首次锁定小数第一位 Alan Li、Rahul Saha 等七位研究者发布两篇配套预印本,给出 Grothendieck 常数的新界:6π/11≤K_G≤1.7818666069360661。这个常数刻画一类困难离散优化问题与其可在多项式时间求解的半定规划松弛之间,最坏情况下会相差多少,也联系矩阵 cut norm、Banach 空间几何和量子关联。此前已知范围约为 1.6769566742 至 1.7822139782;新结果把区间收窄约 35%,首次确定 K_G 的小数第一位是 7。 数学上的两项变化分别来自不同方向:新下界不再构造一个具体“困难实例”,而是证明任意 Krivine 舍入方案的相关函数系数满足约束,再借已有最优性定理推出 6π/11;新上界则构造随维度增长的 limiting Krivine scheme,给出高维方案确实能改善经典界的首个结果。作者公

12 Aug 2026, 02:03 UTC477 views1 reactionsread 13 August 2026
Photo

Google AMIE 扩展到实时视频问诊:100 个模拟病例中超过医生对照 Google Research 与 Google DeepMind 公布 AMIE Video。系统基于 Gemini 3 Flash、Gemini 3.1 Pro 和 Project Astra,让 Talker、Planner、Perception 三个智能体异步协作,在视频通话中进行语音对话、识别视听线索,并引导患者完成远程体格检查。 在随机化模拟研究中,15 名专业患者演员围绕 100 个病例,分别完成 AMIE 视频、AMIE 文本和全科医生视频三组共 300 次问诊;10 名美国认证全科医生参与对照,另有 20 名独立认证医生评审。 AMIE 视频组病例专属量表总分为 83%,医生组为 68%(经 FDR 调整 p=1.32×10⁻⁹);首位诊断命中率为 91% 对 77%(p=.039),感知与检查得分为 74% 对 47%。相较

👍1

11 Aug 2026, 13:46 UTC536 views1 reactionsread 13 August 2026
Photo

NVIDIA 发布 Nemotron 3.5 Lightning,并介绍 NeMo Switchyard NVIDIA 正式发布面向长时运行智能体执行层的 Nemotron 3.5 Lightning。模型采用 Mamba-2、混合专家与少量 Attention 层交错的架构,总参数 300 亿、每个 token 约激活 30 亿参数,预训练超过 20 万亿 token。NVFP4 固定配置支持最高 100 万 token,BF16 参考权重配置为 26.2 万 token。 Hugging Face 已提供 Base BF16、后训练 BF16、NVFP4,以及 DFlash、DSpark 两个推测解码模型。后训练 BF16 权重约 61.3GiB,NVFP4 约 20.1GiB;官方给出 vLLM、TensorRT-LLM 和 SGLang 部署路径。模型材料采用 OpenMDW-1.1 许可证。 NVIDIA 模型卡

1

11 Aug 2026, 13:00 UTC114 viewsread 13 August 2026
Photo

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11 Aug 2026, 09:45 UTC528 viewsread 13 August 2026

OpenAI Agents SDK 双端升级:默认切换 GPT-5.6 Luna,并接入 MCP 2026-07-28 OpenAI 同日发布 Agents SDK Python 0.20.0 与 JavaScript 0.15.0。应用未显式指定模型时,两端默认值都由 gpt-5.4-mini 改为 gpt-5.6-luna;显式模型、运行级覆盖和 OPENAI_DEFAULT_MODEL 仍优先。 MCP 集成同步升级:JS 改用 MCP TypeScript client 2.0,stdio 与 Streamable HTTP 会探测 server/discover,支持时进入 2026-07-28 最终协议,否则回退旧版 initialize。Python 同时兼容已安装的 MCP SDK v1/v2,v2 路径使用自动协商。 双端 RunState 现在可持久化暂停期间的新输入,并只在下一次安全模型请求前接纳;工

11 Aug 2026, 01:42 UTC586 views0 reactionsread 13 August 2026

【OpenAI 推出 GPT‑5.6 Cyber:仅向 Daybreak Red 获批防御者开放】 OpenAI 8 月 10 日推出网络安全专用模型 GPT‑5.6 Cyber,并把 Daybreak Access 分为 Blue 与 Red 两级。Blue 基于 GPT‑5.6 Sol,面向漏洞分诊、安全代码审查、恶意软件分析、事件响应与补丁验证;Red 面向获授权的漏洞研究、漏洞利用验证、渗透测试和红队工作,可使用专门训练、降低高风险双用途任务拒答率的 GPT‑5.6 Cyber。 该模型已经向通过 Daybreak Red 单独审批和配置的个人及机构开放。API 模型 ID 为 gpt-5.6-cyber,稳定访问别名为 gpt-daybreak-red;既有 Trusted Access 或 GPT‑5.5 Cyber 权限不会自动升级。官方模型页列出 40 万 token 上下文、12.8 万最大输出;每百万 t

10 Aug 2026, 13:00 UTC190 viewsread 13 August 2026
Photo

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10 Aug 2026, 04:38 UTC725 viewsread 13 August 2026
Photo

Claude Code 将于 8 月 14 日默认启用 Auto mode Anthropic 宣布,从 2026 年 8 月 14 日起,Claude Pro、Max 和 Team 计划的新 Claude Code 会话将默认以 Auto mode 启动。尚未设置默认权限模式的用户会收到产品内通知;已经自行选择其他默认模式的用户,可能只会看到一次是否切换的询问;由组织管理员固定的默认值不会改变。 Auto mode 不再让用户逐条点击常规权限提示,而是让独立分类器判断可能不可逆、破坏性或越过环境边界的动作。明确的 ask/deny 规则仍先执行;连续阻断 3 次或单会话累计 20 次后,Claude Code 会恢复人工审批。企业管理员现在即可通过 managed settings 设为组织默认或完全禁用。 Pro、Max 和 Team 用户的分类器额外 token 从 8 月 7 日起不再计费。Enterprise、C

10 Aug 2026, 03:43 UTC654 viewsread 13 August 2026

SWE-bench 将 v5 评测框架合入主分支:评测环境转向数据集驱动 SWE-bench 官方于北京时间 8 月 10 日清晨将长期开发的 v5 评测框架合并进主分支,源码内部版本号标记为 5.0.0rc。本次合并涉及 68 个文件,新增约 1850 行、删除约 8338 行。核心变化是把评测环境从框架依据各语言 Python 常量与模板生成,改为由每条数据记录直接携带镜像名、评测脚本、日志解析器和评测类型。 新架构把 base→env→instance 三层镜像收敛为每个任务一个自包含镜像,镜像构建逻辑移入 image_builder,并加入更长的 Docker 操作超时、残留容器清理和无补丁基线运行选项。同一时间窗口内,SWE-bench、Lite、Verified、Multilingual 与 Multimodal 五套官方 Hugging Face 数据集同步加入四个 v5 字段,并把 image 字段指向已发布

9 Aug 2026, 13:00 UTC313 viewsread 13 August 2026
Photo

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9 Aug 2026, 05:47 UTC776 views1 reactionsread 13 August 2026

Cline 四端同步更新:中止后保住队列与会话上下文 Cline 在约两小时内依次发布 SDK 0.0.72、CLI 3.0.52、VS Code 4.1.7 与 Desktop 0.0.11,四个版本沿同一条提交链共享一组 Agent 运行时修复。用户在一轮执行中排队的新提示,即使当前轮被主动中止也会保留;自中止完成后队列继续排空,失败的排队轮则明确上报 run.failed。中止轨迹会先写入持久会话,因此 hub 重启后恢复时不再退回重置上下文。 Checkpoint 现在能从 stash 的第三个 parent 读取快照时尚未跟踪的文件,执行中途初始化 Git 的项目也会被纳入,使完成卡片上的 View Changes 覆盖更完整的任务改动。MCP 初始化改为有限等待;插件设置与贡献集中到 hub,source host 优先使用自己的 TypeScript sandbox bootstrap。 CLI 还新增 cl

1

Showing the 12 most recent of 38 posts we hold for @ShareCentre. 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

Citation-graph rank — 111,963 of 1,169,250entries 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.

Forward network

Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.

Mentions

Named by 6 registered channels — 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.

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 11 August 2026 — this entry's latest reading, not the date you are reading this.

“AI一线|ShareCentre” (@ShareCentre), 15,511 subscribers as measured 11 August 2026. Telegram Register, tgregister.com/channel/ShareCentre.

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.