Telegram RegisterThe public register of Telegram
Telegram profile photo for ChatGPT 精选

Channel

ChatGPT 精选

@AwesomeChatGPT

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry

15,157subscribers

+427 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-1001967944554
TypeChannel
Username@AwesomeChatGPT
DescriptionChatGPT 精选资源
CreatedBetween 1 April 2023 and 31 October 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live6 November 2026
Measurements held57
Confirmed unchanged1 time, most recently 6 November 2026
On Telegramt.me/AwesomeChatGPT

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 10 September 2026 and assigned it the closest of 31 fixed categories, at 99% 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 the other topics.

Growth

14,73015,16414,9476 August 2026 — 14,730 subscribers6 August 2026 — 14,730 subscribers7 August 2026 — 14,734 subscribers8 August 2026 — 14,740 subscribers9 August 2026 — 14,742 subscribers10 August 2026 — 14,744 subscribers11 August 2026 — 14,749 subscribers14 August 2026 — 14,764 subscribers15 August 2026 — 14,771 subscribers16 August 2026 — 14,788 subscribers17 August 2026 — 14,790 subscribers18 August 2026 — 14,795 subscribers20 August 2026 — 14,817 subscribers20 August 2026 — 14,822 subscribers22 August 2026 — 14,828 subscribers23 August 2026 — 14,827 subscribers25 August 2026 — 14,838 subscribers26 August 2026 — 14,850 subscribers27 August 2026 — 14,855 subscribers28 August 2026 — 14,860 subscribers29 August 2026 — 14,873 subscribers29 August 2026 — 14,880 subscribers30 August 2026 — 14,881 subscribers1 September 2026 — 14,872 subscribers2 September 2026 — 14,881 subscribers3 September 2026 — 14,888 subscribers4 September 2026 — 14,894 subscribers7 September 2026 — 14,906 subscribers10 September 2026 — 14,915 subscribers12 September 2026 — 14,929 subscribers14 September 2026 — 14,934 subscribers15 September 2026 — 14,960 subscribers18 September 2026 — 15,061 subscribers30 September 2026 — 15,034 subscribers5 October 2026 — 15,063 subscribers10 October 2026 — 15,060 subscribers13 October 2026 — 15,085 subscribers14 October 2026 — 15,083 subscribers17 October 2026 — 15,088 subscribers18 October 2026 — 15,096 subscribers19 October 2026 — 15,097 subscribers21 October 2026 — 15,100 subscribers22 October 2026 — 15,106 subscribers23 October 2026 — 15,111 subscribers24 October 2026 — 15,115 subscribers25 October 2026 — 15,117 subscribers26 October 2026 — 15,114 subscribers27 October 2026 — 15,120 subscribers28 October 2026 — 15,124 subscribers29 October 2026 — 15,126 subscribers30 October 2026 — 15,139 subscribers31 October 2026 — 15,147 subscribers1 November 2026 — 15,151 subscribers2 November 2026 — 15,160 subscribers3 November 2026 — 15,162 subscribers4 November 2026 — 15,164 subscribers6 November 2026 — 15,157 subscribers15,1576 August 20266 November 2026
57 measurements spanning 92 days, net +427. 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 14,665–15,229 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 57
Measured (UTC)SubscribersChange
6 Nov 2026, 14:0615,157-7
4 Nov 2026, 13:3715,164+2
3 Nov 2026, 12:3015,162+2
2 Nov 2026, 14:3915,160+9
1 Nov 2026, 11:3515,151+4
31 Oct 2026, 11:5915,147+8
30 Oct 2026, 09:5015,139+13
29 Oct 2026, 12:4415,126+2
28 Oct 2026, 08:1615,124+4
27 Oct 2026, 10:1815,120+6
26 Oct 2026, 06:5515,114-3
25 Oct 2026, 07:5415,117+2
24 Oct 2026, 09:2715,115+4
23 Oct 2026, 10:5115,111+5
22 Oct 2026, 10:0415,106+6
21 Oct 2026, 04:1715,100+3
19 Oct 2026, 02:1815,097+1
18 Oct 2026, 01:5615,096+8
17 Oct 2026, 00:2615,088+5
14 Oct 2026, 23:4115,083first reading

Engagement

33 posts held, back to 2 May 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 62 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
9.22%
avg views ÷ 15,157 subscribers
Avg views / post
1,400
3 posts measured
Reaction rate
0.117%
reactions ÷ views · ER floor
Posts in window
3
of 33 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 1 of 3 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 7 November 2026
Posts held33 (2 May 2026 – 7 November 2026)
Views total4,192
Reactions total4
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Nov 2026, 05:37 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
≈1,980
Videos
≈90
Links
≈1,800

Lifetime counters from Telegram’s own channel header, read 7 November 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
10m 55s
Average length
5m 28s

Measured directly from 2 videos 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

98 reactions across 19 posts, in 4 distinct kinds. The most used accounts for 94.9% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤9394.9%
👍33.06%
💩11.02%
🤣11.02%

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 23 of the 33 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 98 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 33 most recent posts we hold, published 2 May 2026 to 7 November 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

Telegram’s own ‘edited’ marker: 0 of 3 posts held from the last 30 days (0%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).

7 Nov 2026, 01:09 UTC282 viewsread 7 November 2026

Google 发布 Gemini Omni 1.2 Flash:原生视频最长从 10 秒增至 15 秒(11 月 5 日)。 更实用的是多轮对话编辑:生成后继续要求换背景、调光线或改画幅,逐步修改同一段视频。已在 Gemini API 和 Gemini for business 正式开放。 https://blog.google/innovation-and-ai/technology/developers-tools/introducing-gemini-omni-1-2-flash/ #AI视频 #Gemini

Signed Eric Hi

6 Nov 2026, 15:48 UTC500 viewsread 7 November 2026

让 AI Agent 接手桌面操作:Vercel Labs 开源了 agent-desktop。 通过系统无障碍树读取按钮、输入框,再按元素点击、输入并检查结果。支持 macOS、Windows、Linux,提供 CLI 和 MCP 接口,本身不内置模型。 适合探索跨应用自动化;效果取决于应用的无障碍支持。 https://github.com/vercel-labs/agent-desktop #AI工具 #Agent #开源

Signed Eric Hi

13 Oct 2026, 23:38 UTC≈3,410 views4 reactionsread 7 November 2026
Forwarded from @readhub_cn

Anthropic 强化蒸馏攻击防御,已封禁数万个相关账号 Anthropic 表示新防护措施已使蒸馏攻击者从其平台提取的 Claude 推理 Token 数量减少约 90% 至 99%。攻击者常借助虚假账号网络批量获取模型回复,未经授权复制其能力,完整推理记录比最终答案更具训练价值。新措施包括限制推理记录在对话、模型及账号间转移,部署两阶段分类器识别和拦截提取请求,对反复尝试的账号限流或封禁,分类器误报率低于 0.1%,已封禁数万个相关蒸馏账号,通常在攻击开始后两小时内完成封禁。此外公司自 9 月 24 日起恢复对蒸馏等特定类别中被安全防护拦截的请求收费,部分开发者需更新集成方式,分类器也可能误拦正常请求。目前防护成效的持续时间尚不明确,公司尚未遭遇高度复杂且持续性的绕过尝试,仍需不断迭代防御措施。 媒体报道 Anthropic 强化蒸馏攻击防御,已封禁数万个相关账号 theblockbeats.info Anthropi…

❤3👍1

Signed Eric Hi

7 Oct 2026, 09:44 UTC≈4,140 views3 reactionsread 7 November 2026
Forwarded from @xhqcankao

黑客利用中国AI工具攻击韩国金融业,暴露新风险 官员们表示,黑客利用一个中国AI智能体攻击了韩国最大的几家银行,并窃取了 6.8 万人的个人信息,这是全球金融系统最早遭遇的此类由AI驱动的入侵事件之一。首尔的调查人员表示,这些攻击最初于上周被发现,袭击了至少七家韩国金融公司,并留下了名为 Artex AI的中国产网络安全工具的活动痕迹。韩国警察厅网络反恐部门周二表示,已对此次数据泄露事件展开调查。Artex是个开源AI智能体,由化名为Autumn的中国网络安全工程师 Li Puhua 开发。Li专门为网络安全用途设计了Artex,旨在帮助各组织识别其网络中的漏洞。然而,在本次事件中,官员认为恶意黑客利用该工具侵入了银行系统。 —— 华尔街日报

❤3

Signed Eric Hi

7 Oct 2026, 09:43 UTC≈3,800 viewsread 7 November 2026
Forwarded from @solidot

Anthropic 举报了与 Claude 聊天中发出威胁的佛罗里达女子 2026-10-06 22:11 by 奇岛 Anthropic 举报了一名佛罗里达女子,原因是这名女子在与 Claude 聊天中威胁要枪击 Lee 县警长办公室,并在后续聊天中提及自己正在搞一把新枪。该女子在家中被捕,法庭记录显示她于 9 月 30 日受到了一项重罪指控。逮捕报告显示,Anthropic 会监控聊天内容,查找可能被视为有威胁性的关键词句,根据威胁程度相关内容可能会被提交给人工进行审核。在本案中,审核团队决定将发现的情况报告给执法部门。她的罪名是通过书面或电子形式发出大规模枪击或恐怖主义行动的威胁。 https://yro.slashdot.org/story/26/10/05/1733245/anthropic-reports-florida-womans-claude-diary-threat-to-law-enforcement…

Signed Eric Hi

20 Aug 2026, 01:03 UTC≈7,640 views3 reactionsread 7 November 2026
Forwarded from @githubtrending

#python #audiobook #faster_whisper #gradio #karaoke #podcasts #speech_recognition #speech_synthesis #speech_to_text #subtitles #text_to_speech #transcription #translator #tts #voice_cloning #voice_conversion #webui #whisper #whisperx #yt_dlp Voice-Pro is a free, open-source Windows app that lets you download YouTube videos, separate voices, turn speech into text, translate into 100+ languages, and create new speech …

❤3

Signed Eric Hi

20 Aug 2026, 01:02 UTC≈5,920 views2 reactionsread 7 November 2026
Forwarded from @githubtrending

#python #ai #assistant #language_model #machine_learning #python #speech #speech_synthesis #speech_to_text #speech_translation I can help you build a fast, modular voice agent that turns speech into text, sends it to a language model, then speaks the answer back. It works with open-source or hosted models, can run fully local on your own hardware, and supports live transcription and low-latency conversation, so you …

❤2

Signed Eric Hi

18 Aug 2026, 01:32 UTC≈4,990 views5 reactionsread 7 November 2026
Forwarded from @https1024Photo

让整个公司共用一个智能体:每个人有自己的隔离工作区,也能在频道和项目里一起协作,而不是各养各的个人助理。 https://github.com/yc-software/qm QM 是 Y Combinator 开源的多人智能体框架,给初创公司用。每个员工有自己的隔离工作区,也能在 Slack 频道、群聊、项目里和智能体协作;人和房间各自带作用域,记忆、文件、密钥、权限、定时任务、Web 应用和持久化沙箱,互不干扰。 核心是无头 TypeScript/Node 服务,harness 和模型走接口,Pi、OpenCode、Codex、Claude Code 随时换 互联网充电|优质资源 优质内容|内幕消息

❤5

Signed Eric Hi

18 Aug 2026, 01:30 UTC≈4,140 views2 reactionsread 7 November 2026
Forwarded from @xhqcankao

AI“养蛊”早期观察:Anthropic警告智能体为争夺地盘相互谋划“暗杀” Anthropic上周公布了一份新的测试研究,讨论了人工智能智能体在实际环境中群体协作可能会采取的行为模式,结果发现这些智能体很可能发展成一群“暴徒”。 在一项实验中,Anthropic公司让多个智能体访问同一个软件项目,每个智能体都拥有各自不同的操作指令。这些智能体事先并不知道会有其他智能体也在使用同一个项目。 研究人员指出,持续观察到智能体之间的地盘争夺战,且所有智能体都假定其他智能体故意阻碍它们的工作,并越来越倾向于使用更具攻击性、能够自我复制的恶意软件互相破坏。研究人员警告,在共享环境中,单个智能体的不良行为可能演变为系统性风险。 —— 财联社

❤2

Signed Eric Hi

18 Aug 2026, 01:24 UTC≈3,380 viewsread 7 November 2026
Forwarded from @xhqcankao

亚马逊采购珍稀书籍拆解后用于AI训练 亚马逊正在大量购买书籍,扫描它们以获取AI训练数据,并在此过程中销毁它们。媒体调查得以揭露亚马逊的书籍采购操作,方法是在一本认为会被AI公司收购用于训练数据的稀有书籍中放置一个追踪设备,并跟随它穿越全国到达其最终目的地。 那个最终目的地是位于内华达州拉斯维加斯的一个亚马逊仓库。在这个地点工作的亚马逊员工表示,他们所做的就是接收大量装运的印刷书籍,然后切掉书脊,以便更快地扫描这些书。印刷书籍在此过程中被销毁。 “亚马逊通过商业渠道购买书籍,以帮助开发和改进我们的客户使用的产品和服务,”一位亚马逊发言人在一份声明中说道。 —— 404media

Signed Eric Hi

18 Aug 2026, 01:21 UTC≈2,880 viewsread 7 November 2026
Forwarded from @xhqcankao

谷歌将允许从AI生成内容中移除可见水印 谷歌于周五宣布,现在将允许用户从其AI生成内容,包括图像、视频和歌曲中移除可见水印。该公司明确指出,这不会影响不可见的SynthID水印以及与C2PA标准相关的元数据。该公司负责 Gemini 的副总裁乔什·伍德沃德在社交平台 X 上的一篇帖子中表示,此切换开关将适用于 Nano Banana、Omni 以及Lyria模型。他明确说明,关闭可见水印的设置将在Gemini和谷歌的视频编辑器 Flow 中提供,对Search的支持也即将推出。 这项功能将在未来几天内逐步推出,一旦可用,用户将能够前往“设置”>“媒体水印”来打开或关闭可见标记。 —— Techcrunch

Signed Eric Hi

18 Aug 2026, 01:15 UTC≈2,550 views0 reactionsread 7 November 2026
Forwarded from @AI_News_CN

Anthropic 分享 Claude Code 六大省钱技巧,提示缓存可省 90% 成本 Anthropic 发布博客,分享 Claude Code 6 大省钱技巧:修完任务就 /clear 清空对话;开局锁定模型和推理强度,避免切换使提示缓存失效;用 @ 引用文件而非手打路径;给输出多的命令加静默参数;休息前执行 /compact;把大输出任务交给子 Agent。 官方称输出 token 比输入贵 5 倍,而提示缓存命中后读取仅需正常输入价 0.1 倍,可省 90%。开发者日均消耗约 13 美元 token。 6 大技巧总结: 1. 在不同任务之间运行 /clear。这样可以避免把之前无关的上下文继续发送给模型,从而减少 Token 消耗。 2. 开始工作前,先确定好模型和推理强度。中途更改其中任何一个,都可能导致提示词缓存失效,进而增加 Token 成本。 3. 不要只写出文件名,而是直接用 @ 提及文件。这样…

Signed Eric Hi

Showing the 12 most recent of 33 posts we hold for @AwesomeChatGPT. 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.

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 2 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.

Named by

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

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.

Appears in Telegram’s recommendations for other channels

The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.

ChatGPT / AI新闻聚合
@AI_News_CN · 23,185
Telegram ranks this channel #2 of 45 here — alongside 44 others — read 22 September 2026
PPbuzz | PP分享🧚
@ppbuzz_pro · 37,967
Telegram ranks this channel #10 of 20 here — alongside 19 others — read 1 September 2026
ahhhhfs|A姐分享
@abskoop · 303,921
Telegram ranks this channel #13 of 50 here — alongside 49 others — read 17 August 2026
极客分享
@geekshare · 65,414
Telegram ranks this channel #19 of 44 here — alongside 43 others — read 21 August 2026
📖Telegram数字图书馆
@TG_book_data · 30,431
Telegram ranks this channel #28 of 44 here — alongside 43 others — read 8 September 2026
黑洞资源笔记
@piracy6 · 77,976
Telegram ranks this channel #35 of 61 here — alongside 60 others — read 19 August 2026
黑科技软件资源分享
@kkaifenxiang · 261,600
Telegram ranks this channel #36 of 39 here — alongside 38 others — read 19 August 2026
Widget🏂软件工具资源分享
@WidgetChannel · 106,905
Telegram ranks this channel #39 of 44 here — alongside 43 others — read 17 August 2026
外滩读书会-最新报纸、杂志、财经报告及流行电子书分享
@readingclubus · 28,795
Telegram ranks this channel #40 of 41 here — alongside 40 others — read 8 September 2026
科技&趣闻&杂记
@kejiqu · 36,769
Telegram ranks this channel #44 of 48 here — alongside 47 others — read 1 September 2026
即刻精选
@jike_collection · 35,855
Telegram ranks this channel #48 of 48 here — alongside 47 others — read 2 September 2026
股市宏观策略行业研报 A股票
@hgclhyyb · 19,853
Telegram ranks this channel #54 of 54 here — alongside 53 others — read 1 October 2026

This channel appears in 12 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.

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 6 November 2026 — this entry's latest reading, not the date you are reading this.

“ChatGPT 精选” (@AwesomeChatGPT), 15,157 subscribers as measured 6 November 2026. Telegram Register, tgregister.com/channel/AwesomeChatGPT.

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.