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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

15,061subscribers

+331 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
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 live18 September 2026
Measurements held33
Confirmed unchanged1 time, most recently 18 September 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 why it has no browse page of its own yet.

Growth

14,73015,06114,895.56 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 subscribers6 August 202618 September 2026
33 measurements spanning 42 days, net +331. 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 14,680–15,111 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 33
Measured (UTC)SubscribersChange
18 Sept 2026, 04:1715,061+101
15 Sept 2026, 22:3814,960+26
14 Sept 2026, 06:5914,934+5
12 Sept 2026, 18:5514,929+14
10 Sept 2026, 20:5614,915+9
7 Sept 2026, 18:5914,906+12
4 Sept 2026, 18:0114,894+6
3 Sept 2026, 00:3714,888+7
2 Sept 2026, 00:2314,881+9
1 Sept 2026, 00:0714,872-9
30 Aug 2026, 22:4814,881+1
29 Aug 2026, 22:1914,880+7
29 Aug 2026, 01:4514,873+13
28 Aug 2026, 00:4314,860+5
27 Aug 2026, 03:3614,855+5
26 Aug 2026, 06:3314,850+12
25 Aug 2026, 02:5814,838+11
23 Aug 2026, 18:5514,827-1
22 Aug 2026, 00:5614,828+6
20 Aug 2026, 22:1114,822first reading

Engagement

28 posts held, back to 2 May 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 53 pages of Telegram’s post history, 20 posts per page.

Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 28 posts for this entry, the most recent from 20 August 2026. An engagement rate over an empty window would be a number about nothing.

What this channel posts

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

80 reactions across 16 posts, in 4 distinct kinds. The most used accounts for 95.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
7695.0%
👍22.50%
💩11.25%
🤣11.25%

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 19 of the 28 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 80 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 28 most recent posts we hold, published 2 May 2026 to 20 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

20 Aug 2026, 01:03 UTC≈2,030 viewsread 3 September 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

Signed Eric Hi

20 Aug 2026, 01:02 UTC≈1,710 views1 reactionsread 3 September 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

1

Signed Eric Hi

18 Aug 2026, 01:32 UTC≈1,870 views3 reactionsread 3 September 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

3

Signed Eric Hi

18 Aug 2026, 01:30 UTC≈1,580 views1 reactionsread 3 September 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

1

Signed Eric Hi

18 Aug 2026, 01:24 UTC≈1,300 viewsread 3 September 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≈1,160 viewsread 3 September 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≈1,050 viewsread 3 September 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

18 Aug 2026, 01:14 UTC977 viewsread 3 September 2026
Forwarded from @AI_News_CNPhoto

速度狂飙 14 倍!OpenAI重磅推出GPT-5.6 Sol UltraFast超快模式,每秒最高狂飙750tokens OpenAI日前正式面向企业用户推出了全新的 GPT-5.6Sol UltraFast 超快模式预览。借助该模式,模型的运行速度得到了颠覆性的提升,最高可达标准模式的14倍,每秒最多能够生成高达750个tokens。 据了解,这一超快模式的核心技术由 Cerebras 提供强力支持。不过,为了确保资源的合理利用,目前该模式暂时采用申请审核制。有需求的企业用户需要向OpenAI提交具体的使用场景申请,是否获批将由官方根据实际情况进行综合评估。 在应用场景方面,OpenAI表示,超快模式并非面向所有常规工作负载,而是专门为那些对实时性有极高要求的业务场景打造。例如:实时语音交互、智能化客户支持、商务应用、开发智能体(Agents)、金融深度研究以及前沿的安全研究等。 随着预览阶段的逐步推进,Cerebr

Signed Eric Hi

18 Aug 2026, 01:13 UTC≈1,250 viewsread 3 September 2026
Forwarded from @AI_News_CNPhoto

百万上下文全面开放,Codex迎来AI编程“终极形态” OpenAI旗下的Codex迎来了重磅更新。负责Codex与ChatGPT的工程师Tibo在社交平台上官宣,备受瞩目的GPT-5.6Sol模型百万Token上下文窗口功能,已经正式向全体ChatGPT账号开放。 此前,这一超大上下文能力仅限API密钥调用。随着该项限制的解除,持有ChatGPT Plus以及Pro等订阅计划的用户,现在只要手动进行配置,就能在Codex编程代理工具中享受到约105万Token的完整上下文窗口。 对于广大开发者而言,这意味着在自动压缩历史信息之前,Codex能够容纳并处理更多代码、工具输出以及完整的对话记录。无论是大型代码库的重构、复杂项目的深度调试,还是长时间的高强度会话,这一特性都带来了极大的便利,彻底解决了以往因上下文不足而影响大项目维护的痛点。 不过,开发团队也给出了善意提醒。当前的默认上下文长度是经过精心调优的折中结果,兼顾了

Signed Eric Hi

18 Aug 2026, 01:13 UTC≈1,440 viewsread 3 September 2026
Forwarded from @AI_News_CN

Claude水印已被破解 斩获11k Star 但会被拒绝安装 via cnBeta.COM - 中文业界资讯站 (author: 稿源:机器之心)

Signed Eric Hi

7 Jun 2026, 00:56 UTC≈9,140 views35 reactionsread 3 September 2026
Forwarded from @dogdairy

一些我个人关于投资的思考笔记: 1) 在一开始做投资练习的时候,都是直觉的,盲目的。 哪怕查了资料,做了分析研究,其实也是虚假的,是不懂的。 这个时候赚到钱是运气,亏了钱是活该。 2) 一个基本原理是“不懂不投”,那怎样算懂? 你对谢霆锋和王菲的八卦是怎样的如数家珍; 对甄嬛传的每句台词和每个人物暗线是怎样的了然于胸; 对爱豆的成长史和背后的经纪公司纠纷是怎样的头头是道。 到这个程度就算是懂。 3) 这样的“懂”,需要的是长期的关注,思考,了解,追踪。 仅仅是用AI查一下,看了一点财报,甚至只是看了理财app里的介绍,都远远算不上懂。 4) 所以大多数人都是在盲投,哪怕是那些满嘴术语做了很长时间炒股的人,也有很多是在装懂。 5) 这样看来我对任何公司都不懂,咋办? 我应该放弃投资理财吗? 也不是。 虽然你现在不懂,但是你可以“开始懂” 6) 现在开始,学着以投资人的眼光去关注几个领域,几个公司。 跳出消费者视角,站在更高的位置去

35

Signed Eric Hi

7 Jun 2026, 00:32 UTC≈7,800 views3 reactionsread 3 September 2026
Forwarded from @githubtrending

#rust MXC is a sandbox system that runs untrusted code safely on Windows, Linux, and macOS with shared JSON settings and a TypeScript SDK. It helps you control files, network access, and UI use while giving you a safer way to test or run code; this can protect your computer and make automation easier to build. The project is still early preview, so its security rules are not yet final and should not be treated as fu

3

Signed Eric Hi

Showing the 12 most recent of 28 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 · 21,862
Telegram ranks this channel #2 of 45 here — alongside 44 others — read 22 September 2026
PPbuzz | PP分享🧚
@ppbuzz_pro · 37,472
Telegram ranks this channel #10 of 20 here — alongside 19 others — read 1 September 2026
ahhhhfs|A姐分享
@abskoop · 306,586
Telegram ranks this channel #13 of 50 here — alongside 49 others — read 17 August 2026
极客分享
@geekshare · 64,669
Telegram ranks this channel #19 of 44 here — alongside 43 others — read 21 August 2026
📖Telegram数字图书馆
@TG_book_data · 30,452
Telegram ranks this channel #28 of 44 here — alongside 43 others — read 8 September 2026
黑洞资源笔记
@piracy6 · 77,362
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 · 260,900
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 · 99,840
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 · 29,174
Telegram ranks this channel #40 of 41 here — alongside 40 others — read 8 September 2026
科技&趣闻&杂记
@kejiqu · 36,460
Telegram ranks this channel #44 of 48 here — alongside 47 others — read 1 September 2026
即刻精选
@jike_collection · 35,819
Telegram ranks this channel #48 of 48 here — alongside 47 others — read 2 September 2026

This channel appears in 11 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 18 September 2026 — this entry's latest reading, not the date you are reading this.

“ChatGPT 精选” (@AwesomeChatGPT), 15,061 subscribers as measured 18 September 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.