Education — 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 11 September 2026 and assigned it the closest of 31 fixed categories, at 54% 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
30 measurements spanning 43 days, net -107. 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 12,905–13,052 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 30
Measured (UTC)
Subscribers
Change
18 Sept 2026, 16:40
12,922
-17
16 Sept 2026, 11:40
12,939
-9
14 Sept 2026, 16:20
12,948
-4
13 Sept 2026, 05:17
12,952
-5
11 Sept 2026, 07:37
12,957
-4
8 Sept 2026, 09:59
12,961
-11
3 Sept 2026, 07:05
12,972
+14
2 Sept 2026, 00:53
12,958
-11
31 Aug 2026, 00:05
12,969
-4
29 Aug 2026, 23:08
12,973
+1
29 Aug 2026, 01:25
12,972
-7
27 Aug 2026, 23:47
12,979
-2
26 Aug 2026, 23:01
12,981
-7
26 Aug 2026, 00:24
12,988
-5
25 Aug 2026, 02:36
12,993
-1
23 Aug 2026, 20:44
12,994
-3
22 Aug 2026, 08:17
12,997
-8
21 Aug 2026, 00:26
13,005
-14
19 Aug 2026, 22:53
13,019
-8
18 Aug 2026, 20:43
13,027
first reading
Engagement
23 posts held, back to 6 June 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 48 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
9.38%
avg views ÷ 12,922 subscribers
Avg views / post
1,210
6 posts measured
Reaction rate
1.43%
reactions ÷ views · ER floor
Posts in window
6
of 23 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 2 September 2026
Posts held
23 (6 June 2026 – 2 September 2026)
Views total
7,271
Reactions total
104
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
2 Sept 2026, 20:50 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 44s
Average length
21s
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.
Reaction mix
491 reactions across 23 posts, in 25 distinct kinds. The most used accounts for 45.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
223
45.4%
❤
148
30.1%
⚡
28
5.70%
👍
26
5.30%
🤬
12
2.44%
🤯
9
1.83%
👏
8
1.63%
custom 5415655814079723871
5
1.02%
✍
5
1.02%
👎
4
0.815%
custom 5456140674028019486
3
0.611%
🙏
3
0.611%
👾
2
0.407%
😁
2
0.407%
😍
2
0.407%
🤩
2
0.407%
☃
1
0.204%
❤🔥
1
0.204%
🆒
1
0.204%
🎄
1
0.204%
5 further kinds
5
1.02%
Custom emoji. 2 of the rows above are Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The counts beside them are Telegram’s.
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 23 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 491 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 23 most recent posts we hold, published 6 June 2026 to 2 September 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
11
across the posts below
Posts paid on
4
of 23 we hold a reading for · 17%
Most on one post
7
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @align_go. 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 23 most recent posts we hold for this entry, published 6 June 2026 to 2 September 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.
30 уроков по ИИ за 30 дней. Бесплатно
Я создал отдельный youtube-канал под Коробку😀 и весь сентябрь буду выкладывать по одному уроку в день
Два уже там:
1. Как Claude Cowork нашёл 52 ГБ мусора на моём ноутбуке
2. Создание 3D-видео для shorts в Higgsfield
Это не нарезки и не тизеры, а настоящие уроки с платформы. Конечно, это только малая часть всего контента Коробки, но каждое видео обучает конкретному навыку. Смо…
Как принять оплату от клиента в США или Европе?
Зарубежные компании часто не могут просто перевести деньги на личную карту или криптой: их бухгалтерии нужен официальный договор и инвойс
И с этим помогает Mellow
Вы выставляете клиенту счёт от юрлица Mellow в ЕС или США, он оплачивает его обычным банковским переводом, а вы выводите деньги на карту, банковский счёт или электронный кошелёк
В сервисе есть функция безо…
Разработчик за три часа собрал сайт, и через неделю заработал больше $200 тысяч
Идея простая до предела: платишь больше конкурента, встаёшь выше в списке. Тебя перебили ставкой, платишь снова. Никаких лайков, алгоритмов, голосований. Только деньги решают, кто наверху.
И это взорвало весь твиттер. Причём не просто взорвало, за неделю у этого сайта было более миллионо посетителей и появились уже сотни клонов под свои…
Google Gemini научился создавать интерактивные 3D-модели
Для преподавателей, студентов и всех, кто изучает сложные процессы, это просто незаменимая фича
Теперь Gemini умеет генерировать интерактивные 3D-модели физических и биологических систем: от двойной спирали ДНК и кристаллической решетки до масштабной симуляции планет Солнечной системы
Что внутри:
1. Интерактив и панель управления
Вы получаете не статичную …
Создаем стикерпаки в Whatsapp / Telegram со своим лицом в ChatGPT за 2 клика
В ChatGPT вышло крутое обновление, встроенный конструктор стикеров
Как это работает:
1. Выбираем стиль: Заходим в раздел Изображения, вкладка Стикеры. На выбор доступны разные стили (аниме, чиби, мем, 3D, хром итд)
2. Загружаем фото: Добавляем селфи или фото друзей из галереи или делаем снимок на камеру
3. Задаем эмоции: Выбираем нужны…
😀 Anthropic только что выпустили свою Claude Академию, где обучают пользоваться всеми их продуктами: начиная от Claude, Cowork, Code, до того, как правильно внедрять Claude API на свои сервисы
Это те же самые материалы, по которым обучаются сотрудники в их компании (по их заявлению)
Если давно откладывали обучение по Claude, то самое время начать
🔗 Ссылка на академию
@align_go
Как создавать карусели для соцсетей в любом стиле с ИИ?
Если вы хотите регулярно делать контент в Instagram и TikTok, но вам лень постоянно снимать рилсы или часами сидеть в Figma, появился отличный инструмент
В ChatPlace (раздел Virale) теперь можно генерировать полноценные карусели буквально по одному промпту:
Копирование вашего стиля
Можно скинуть скриншот или пример своей старой карусели (или подробно описать …
Теперь в ChatGPT можно создавать изображения сразу с прозрачным фоном
То есть делать готовые стикеры, элементы для презентаций, сайта или любого другого дизайна без лишней возни с фоном
Либо можно отправить обычное изображение, и попросить его убрать фон
Но ещё полезнее другое обновление, редактирование изображений через комментарии
Теперь не нужно вручную замазывать или выделять область, которую хотите изменить.…
Теперь вы можете вайбкодить прямо в Google Sheets
Google выпустили новую функцию Sheets Canvas, которая позволяет вам превращать ваши скучные таблички в полноценные мини-приложения: трекеры, канбан-доски, сложные дешборды, где ваша табличка будет выступать базой данных
Данные полностью синхронизируются с вашей табличкой, и вы можете ее шейрить и работать в ней вместе с коллегами
Функция доступна пока что только пл…
Meta выпустила отдельное приложение Meta AI для Mac
и там есть одна функция, ради которой многие сейчас платят по $20 в месяц
Системная диктовка
Работает очень просто: зажимаете горячую клавишу в любом приложении или окне, говорите, и Meta AI превращает вашу речь в текст и сразу вставляет его в активное поле для ввода
То есть можно голосом писать письма, сообщения, заметки, документы или промпты в любом месте
Сей…
Скоро мы перестанем платить за половину своих подписок
Если вы умеете вайбкодить, то вместо очередных $10–20 в месяц можно просто завайбкодить нужный инструмент самостоятельно.
И чтобы не гадать, как написать промпт, ловите сайт, на котором собраны сотни популярных инструментов. Для каждого из них сайт показывает:
— можно ли полностью заменить его самостоятельно
— сколько времени займёт разработка
— что будет рабо…
Реально бесплатный API для генерации голоса
Fish Audio только что открыли бесплатный доступ к своей самой продвинутой модели генерации голоса
Она умеет:
— клонировать голос по короткой записи
— озвучивать текст на 83 языках, включая русский
— сохранять голос при смене языка
— управлять эмоциями, темпом и интонацией
— генерировать озвучку для роликов, подкастов и аудиокниг
Как получить полный бесплатный доступ
1.…
🔥14❤5⚡1👏1
Showing the 12 most recent of 23 posts we hold for @align_go. 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.
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 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.
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.
Handles this channel named that no longer answer
Dead references
1
handles named in this channel’s posts, vacant today
Evidenced gone
1
we ourselves saw one of these resolve, at some point
Never seen alive
0
vacant every time we have ever looked
@align_go named 1 handle that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Evidenced gone
We ourselves saw each of these resolve to a real page at some point before it went vacant — a genuine, evidenced change, not an inference from absence.
@poehali_news named in 6 posts, 8 August 2026 – 15 August 2026 · confirmed gone 13 September 2026 (two independent sightings — see how we confirm a dead handle)evidenced
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.
“Alish Go” (@align_go), 12,922 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/align_go.
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.