10 measurements spanning 22 days, net +499. 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 8,518–9,167 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
29 Aug 2026, 18:53
9,092
+27
26 Aug 2026, 08:46
9,065
+33
23 Aug 2026, 18:43
9,032
+21
20 Aug 2026, 13:17
9,011
+13
17 Aug 2026, 19:18
8,998
+88
14 Aug 2026, 18:15
8,910
+88
11 Aug 2026, 06:11
8,822
+228
7 Aug 2026, 20:24
8,594
+1
7 Aug 2026, 19:01
8,593
no change
7 Aug 2026, 18:54
8,593
first reading
Engagement
12 posts held, back to 30 July 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 28 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
21.6%
avg views ÷ 9,092 subscribers
Avg views / post
1,960
9 posts measured
Reaction rate
0.821%
reactions ÷ views · ER floor
Posts in window
9
of 12 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.
What these figures were computed from
Window
Rolling 30 days · latest post in window 26 August 2026
Posts held
12 (30 July 2026 – 26 August 2026)
Views total
17,670
Reactions total
145
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
28 Aug 2026, 15:29 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
Video runtime
1m 40s
Average length
13s
Measured directly from 8 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
206 reactions across 12 posts, in 4 distinct kinds. The most used accounts for 53.9% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
111
53.9%
❤
65
31.6%
👍
23
11.2%
❤🔥
7
3.40%
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 12 of the 12 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 206 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 12 most recent posts we hold, published 30 July 2026 to 26 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.
Telegram Stars
Stars received
2
across the posts below
Posts paid on
1
of 12 we hold a reading for · 8%
Most on one post
2
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @poleznoe_ai. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 12 most recent posts we hold for this entry, published 30 July 2026 to 26 August 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
Как уронить тачку с неба одним промптом? 🚗💨
Без монтажа, без After Effects — два фото и один промпт в Seedance 2.5 и машина падает с неба
Полный гайд с промптом, настройками и разбором ошибок тут 👉 читать гайд
Присылайте в комментах что получилось 💬
@poleznoe_ai 😜
🔥 Как разместить любую рекламу на огромном билборде — без аренды, дизайнера и фотошопа?
Всё, что понадобится:
1️⃣ Фото здания или улицы с пустым рекламным экраном (можно найти на Pinterest)
2️⃣ Готовый дизайн, который хотите разместить
3️⃣ Один универсальный промпт для ChatGPT
Загружаете два изображения в ChatGPT — и нейросеть автоматически подгоняет рекламу под размер, перспективу и освещение билборда.
Она сохра…
🔥 Превращаем одно фото одежды в премиальную рекламу
Для создания такого ролика не нужны модели, студия, оператор и дорогая съёмочная команда. Достаточно одной фотографии продукта и правильно составленного промпта для Google Flow.
Нейросеть сама покажет:
— фактуру ткани крупным планом
— швы и детали изделия
— движение материала
— атмосферу рекламной кампании модного бренда
Я подготовил готовый промпт — просто загр…
А что, если увидеть себя в 15 разных эпохах? 👀
От строгого портрета 1880-х до современного образа из 2020-х
Я приготовил промпт который покажет как бы вы выглядели в разных эпохах
Нейросеть сохраняет черты лица, но полностью меняет:
— одежду и причёску
— освещение
— качество съёмки
— атмосферу каждой эпохи
В итоге получается реалистичная временная шкала в формате музейного архива 🕰️
Загружаете своё фото в ChatGP…
🐉 Как создать видео с рыцарем и драконом?
Подготовил пошаговый гайд, в котором показываю, как повторить этот трендовый ролик со своим лицом.
По сюжету рыцарь спокойно допивает кофе (или любой другой напиток) бросает стакан и камеру за спину. Камера продолжает снимать в полёте, падает на бок — и перед героем появляется спящий дракон. Рыцарь достаёт меч, а дракон открывает глаз ⚔️
Внутри гайда:
— создание карты пе…
ТОП-10 мужских промптов для брутальных фото в ChatGPT 🥷
Пока все генерируют однотипные фотосессии, я собрал подборку кадров, которые выглядят как обложки фильмов и дорогих журналов.
Как повторить со своим лицом:
1. Откройте ChatGPT
2. Загрузите своё чёткое фото как референс
3. Скопируйте промпт под понравившимся кадром
4. Отправьте — и получите похожее фото уже с собой в главной роли
Для лучшего сходства использу…
Озвучить любой текст голосом знаменитости? Легко 🎙
Нашёл сервис Fish Audio, внутри которого собрана огромная библиотека готовых голосов.
Качество некоторых голосов настолько реалистичное, что с первого раза сложно понять, где говорит настоящий человек, а где нейросеть.
Там можно найти:
• популярных актёров и музыкантов
• известных политиков
• персонажей из фильмов, игр и мультфильмов
• голоса на разных языках
Ра…
Видео с распахнутой душой в котором вы показывате свой мир 😌
Собрал подробный гайд, как повторить такой эффект со своим лицом и своим миром.
Внутри — все промпты, настройки и пошаговая инструкция от первого кадра до готового видео.
Забирайте и творите 👉 ССЫЛКА НА ГАЙД
@poleznoe_ai 🙌
С вас лайк если было полезно 💛
Превращаем любую фотографию в кадр из мультсериала 🔥
Нашёл промпт, который переносит человека в узнаваемый стиль американских мультфильмов: выразительные глаза, чёткие контуры, яркие цвета и лёгкая ретро-эстетика.
При этом нейросеть сохраняет:
— внешность и причёску
— одежду и аксессуары
— позу и выражение лица
— композицию и детали исходного кадра
Просто загружаете свою фотографию в Nano Banana, добавляете промп…
Динамичные рекламные Reels, за которые бренды готовы хорошо платить, теперь можно создавать буквально из одной фотографии 🔥
Без сложного монтажа, раскадровки и десятков генераций.
Переходи в VeoSeeBot и выбирай создать видео
Выбирай модель Gemini Omni
Добовляем фото продукта в нейросеть и вставляем промпт
Нейросеть сама превращает обычный кадр в эффектный рекламный ролик с быстрыми переходами, сменой планов и дор…
Я заменил пожарную машину в реальном видео на огромный бигфут🤯
И сейчас хочу поделиться с вами всем процессом (он довольно не сложный)
Подготовил пошаговую инструкцию, в которой показал весь процесс:
• как заменить объект на исходном фото
• как перенести его в готовое видео
• какой промпт использовать, чтобы нейросеть ничего лишнего не изменила
• как добиться максимально реалистичного результата
Забрать инструкци…
Делюсь промптом, который превращает обычную фотографию в настоящий кадр из GTA VI 🌴🔥
Работает практически с любыми фотографиями можно превратить в персонажа игры себя, друга или даже бабушку-диджея 😄
Всё просто:
• загружаете свою фотографию в ChatGPT или Nano Banana
• вставляете промпт
• получаете собственный кадр из GTA 6
Главное - используйте качественное исходное фото, чтобы нейросеть лучше сохранила внешност…
❤🔥7👍3❤2
Showing the 12 most recent of 12 posts we hold for @poleznoe_ai. 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.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
Citation-graph rank
Citation-graph rank — 553,058 of 1,629,452 entries 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
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.
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.
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 29 August 2026 — this
entry's latest reading, not the date you are reading this.
“Полезные Гайды [AI]” (@poleznoe_ai), 9,092 subscribers as measured 29 August 2026. Telegram Register, tgregister.com/channel/poleznoe_ai.
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.