🆔 网站名称:抠抠抠 ⭐ 网站功能:在线抠图 📁 网站简介:一个免费的在线抠图工具,可以通过上传图片轻松去除背景。 支持图片大小不超过3MB,操作简便快速。网站不存储用户的任何数据。 🔗 网站链接:[点击打开]
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Channel
@ai7756
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
20subscribers
+0 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1002249908564 |
|---|---|
| Type | Channel |
| Username | @ai7756 |
| Description | OpenAI ChatGPT |
| Created | Between 1 July 2024 and 8 December 2024— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 11 August 2026 |
| Last confirmed live | 11 August 2026 |
| Measurements held | 2 |
| On Telegram | t.me/ai7756 |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 11 Aug 2026, 16:01 | 20 | no change |
| 7 Aug 2026, 21:32 | 20 | first reading |
17 posts held, back to 8 December 2024 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof 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 17 posts for this entry, the most recent from 8 December 2024. An engagement rate over an empty window would be a number about nothing.
Lifetime counters from Telegram’s own channel header, read 11 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
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.
2 reactions across 2 posts, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 2 | 100.0% |
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 3 of the 17 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 2reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 17 most recent posts we hold, published 8 December 2024 to 8 December 2024, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
🆔 网站名称:抠抠抠 ⭐ 网站功能:在线抠图 📁 网站简介:一个免费的在线抠图工具,可以通过上传图片轻松去除背景。 支持图片大小不超过3MB,操作简便快速。网站不存储用户的任何数据。 🔗 网站链接:[点击打开]
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🆔 项目名称:PuLID ⭐️ 项目功能:AI 图像优化 📁 项目简介:一个开源通过对比对齐技术实现高效的身份定制。优化基于 AI 的图像生成,并提供用户友好的工具和代码示例,以便在普通 GPU 上运行复杂的模型。
🆔 网站名称:懒人图云 ⭐ 网站功能:照片拼图生成器 📁 网站简介:一个专注于照片拼图、图标云和马赛克拼接的在线工具。集成了多款生成器,满足用户在企业照片墙、图标组合、照片马赛克等创意设计中的需求。 🔗 网站链接:[点击打开]
🆔 网站名称:敖武的图床 ⭐ 网站功能:图床 📁 网站简介:一个提供免费图片上传和外链服务的网站,支持多种文件格式上传,包括图片、视频、ZIP和PDF等。 可以通过拖拽或复制粘贴方式轻松上传文件,且上传文件最大支持100M。 🔗 网站链接:[点击打开]
🆔 网站名称:MusicHero ⭐ 网站功能:AI 音乐生成 📁 网站简介:一个免费的在线AI音乐生成平台,通过输入文本描述快速生成高质量的音乐。 利用先进的Suno V3.5技术,将用户的情感、主题或歌词转化为完整的音乐作品,支持多种音乐风格和应用场景。 🔗 网站链接:[点击打开]
🆔 项目名称:auto-video-generateor ⭐️ 项目功能:解说视频生成 📁 项目简介:一款根据用户输入的主题,自动生成解说视频。 系统调用大语言模型生成故事或解说的文字,然后通过语音合成接口生成解说的语音,接着调用文生图接口生成与文字内容相匹配的图片,最终融合语音和图片生成解说视频。
🆔 网站名称:Hostrider ⭐ 网站功能:lo-fi 音乐 📁 网站简介:一只喜欢听 lo-fi 音乐并热爱编程的猫为主题的音乐网站。强调编程作为一种有趣且富有创意的艺术形式,并表达了想要融入一个充满激情的社区的愿望。 🔗 网站链接:[点击打开]
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🆔 项目名称:HivisionIDPhotos ⭐️ 项目功能:AI 证件照制作 📁 项目简介:一个轻量级且高效的 AI 证件照制作工具,能够通过 AI 模型对照片进行抠图、背景替换、生成标准化证件照等操作。 支持离线推理,并且可以在多种设备上运行,包括支持 Docker 部署与 API 服务。
加密货币公司 Goldsky 创始人 Kevin Li 分享了他听到的一个学习方法。 第三条刚开始集中投入十几个小时建立初始印象,然后转入更规律的学习确实很高效。
🆔 项目名称:NarratoAI ⭐️ 项目功能:视频解说和剪辑 📁 项目简介:一款利用AI大模型实现自动视频解说和剪辑功能的开源项目。 为视频创作者提供了一键式的解决方案,包括脚本生成、自动剪辑、语音解说和字幕生成,极大提升了内容创作的效率。
🆔 网站名称:image-beautifier ⭐ 网站功能:截图美化 📁 网站简介:一款开源的在线截图美化工具,支持对截图进行批注、裁剪、局部放大等操作。 预设了各种社交媒体平台的尺寸模板,可以快速调整图片以适合不同平台的发布要求,并可以导出高清图片。 🔗 网站链接:[点击打开]
🎯 Critique Shadowing: 一个让AI稳定输出优质内容的实用工作流 我相信很多AI团队和我们一样,都头疼这个工程问题:如何保证AI生成质量的优质与稳定? fine-tune也好,RAG也好,RL也好,结合具体的业务场景,我们也花了很多精力研究最适用的、更低成本、ROI更高的方法。 不得不说,最近发现的Critique Shadowing 工作流,让我觉得很有启发💡 这个方法来自 Hamel Husain 最新发表的一篇重磅文章🔗
Showing the 12 most recent of 17 posts we hold for @ai7756. 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 — 1,098,020 of 1,151,006entries 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.
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.
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 11 August 2026 — this entry's latest reading, not the date you are reading this.
“AI人工智能” (@ai7756), 20 subscribers as measured 11 August 2026. Telegram Register, tgregister.com/channel/ai7756.
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.