Channel
@centeraieu
On this record: Growth · Engagement · What this channel posts · 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 | -1003973045355 |
|---|---|
| Type | Channel |
| Username | @centeraieu |
| Description | AI automation for business without heavy implementation https://centerai.eu/ We build AI chatbots, business process automations and practical AI assistants that help businesses reply to clients faster |
| Created | Between 1 April 2026 and 11 August 2026— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 11 August 2026 |
| Last confirmed live | 23 August 2026 |
| Measurements held | 2 |
| On Telegram | t.me/centeraieu |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 11 Aug 2026, 15:31 | 20 | no change |
| 7 Aug 2026, 11:18 | 20 | first reading |
20 posts held, back to 11 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 1 pageof 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.
| Window | Rolling 30 days · latest post in window 11 August 2026 |
|---|---|
| Posts held | 20 (11 August 2026 – 11 August 2026) |
| Views total | 20 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 11 Aug 2026, 15:31 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.
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. 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.
Measured directly from 5 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.
🌍 ИИ, который стирает языковые преграды Immersive Translate позволяет удобно читать веб-сайты, просматривать видео и работать с документами на иностранных языках, избавляя от необходимости постоянно копировать текст. Функции:👇 🌐 Переводит целые веб-страницы в браузере, оставляя оригинальный текст рядом с переводом. 💼 Поддерживает перевод PDF, ePub и других форматов документов, сохраняя исходное оформление для PDF…
Использовали ли вы подобные AI-переводчики? Делитесь своим опытом👇
💡 Experience a Cinematic Diner Scene! 🔍 Dive into a photorealistic cinematic scene set in a 1990s American diner, featuring red vinyl booths, neon signage, chrome accents, and a checkerboard floor. The ambiance is enhanced by soft natural light filtering through the windows, complemented by warm practical lighting, subtle handheld textures, and rich period details, all wrapped in a heavy film grain. 📌 0-5s: [Medium…
💡 She literally stopped time to have a peaceful breakfast 🥓 🔍 In Seedance 2.5, they created a 30-second scene straight out of a movie: a girl collides with a waitress, and the tray flies into the air — at the moment of impact, time completely freezes. Coffee hangs in droplets, food stays suspended, and people are frozen in place. Meanwhile, the heroine calmly grabs her bacon and eggs and heads for the exit 👀 The m…
💡 ИИ, который устраняет языковые преграды 🔍 Immersive Translate помогает пользователям читать веб-сайты, смотреть видео и работать с документами на иностранных языках без необходимости постоянного копирования текста. 📌 Что он может: ⚙️ • Переводит целые веб-сайты прямо в браузере, сохраняя оригинальный текст рядом с переводом. ✅ • Обрабатывает PDF, ePub и другие форматы документов, позволяя сохранить исходное офо…
Пользовались такими AI-переводчиками? Делитесь своим опытом!
💡 Tencent Hunyuan has launched WorldClaw — a system that allows an agent to autonomously plan and assemble a 3D world. 😳 🔍 Users simply describe the desired scene. WorldClaw then takes over, planning the landscape, generating buildings, plants, characters, and other objects, and assembling everything in Blender. 📌 Moreover, the system checks the results. If objects are floating, intersecting, or appear disproportio…
💡 Tencent Hunyuan представиха WorldClaw — система, която позволява на агента самостоятелно да планира и събира 3D свят. 😳 🔍 Потребителят просто описва желаната сцена. След това WorldClaw самостоятелно планира ландшафта, генерира сгради, растения, персонажи и други обекти, след което ги събира в Blender. 📌 Системата също така проверява резултата. Ако обектите висят във въздуха, се пресичат или изглеждат несъразмерно…
💡 Hermes Agent Desktop keeps impressing with its updates. 😏 🔍 Recently, a new HUD mode was introduced. Now, Hermes no longer exists as a separate window; it transforms into an overlay on top of the application you are using. 📌 You can keep it nearby as a helpful assistant, move it around the screen, and ask questions while you work. ⚙️ For instance, Hermes can read and summarize posts on X, analyze TradingView cha…
💡 Hermes Agent Desktop продължава да ни радва с нови актуализации. 😏 🔍 Наскоро се появи режим HUD. Сега Hermes вече не е отделен прозорец, а слой над приложението, с което работите. 📌 Можете да го оставите до себе си като помощник, да го местите по екрана и да задавате въпроси в движение. ⚙️ Например, Hermes може да чете и обобщава постове в X, да анализира графики в TradingView и дори да отваря проекти и добавя ф…
💡 A significant new study from Meta. 🔍 Typically, scaling laws suggest that the model size and data volume affect error independently of each other. 📌 In this work, the authors introduce the Skaling law — a principle that connects model capacity and data through a unified interaction parameter. ⚙️ An additional term reduces the average absolute percentage error by about 1.5 to 3 times for both interpolation and ex…
Today, models are often trained and deployed far beyond the classical computationally optimal regime. If the scaling law remains accurate in these contexts and can be evaluated with small runs, it directly alters how pre-training budgets can be planned. Study: https://arxiv.org/abs/2608.07222
Showing the 12 most recent of 20 posts we hold for @centeraieu. 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 — 459,324 of 1,623,166entries 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.
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
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.
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.
“CenterAI — AI automation center for business” (@centeraieu), 20 subscribers as measured 11 August 2026. Telegram Register, tgregister.com/channel/centeraieu.
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.