6 measurements spanning 5 days, net +47. 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 15,242–15,307 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
12 Aug 2026, 05:52
15,299
+5
11 Aug 2026, 04:23
15,294
+18
10 Aug 2026, 02:31
15,276
+22
9 Aug 2026, 00:54
15,254
+5
7 Aug 2026, 21:50
15,249
-3
7 Aug 2026, 01:02
15,252
first reading
Engagement
19 posts held, back to 22 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 18 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
30.1%
avg views ÷ 15,299 subscribers
Avg views / post
4,610
19 posts measured
Reaction rate
0.735%
reactions ÷ views · ER floor
Posts in window
19
of 19 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 12 August 2026
Posts held
19 (22 July 2026 – 12 August 2026)
Views total
87,630
Reactions total
644
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
13 Aug 2026, 01:28 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
Photos
≈1,070
Videos
≈388
Links
≈848
Lifetime counters from Telegram’s own channel header, read 13 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.
Video runtime
7m 06s
Average length
1m 11s
Measured directly from 6 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
644 reactions across 19 posts, in 20 distinct kinds. The most used accounts for 24.2% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
156
24.2%
❤
140
21.7%
👍
98
15.2%
💯
77
12.0%
😁
48
7.45%
🗿
30
4.66%
🤬
26
4.04%
🤣
16
2.48%
custom 5442611071779101206
12
1.86%
🫡
9
1.40%
🤷♂
7
1.09%
👏
6
0.932%
⚡
4
0.621%
😱
4
0.621%
🤔
4
0.621%
👌
3
0.466%
👾
1
0.155%
😭
1
0.155%
🤯
1
0.155%
🥰
1
0.155%
Custom emoji. One row above is a 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 count beside it isTelegram’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 19 of the 19 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 644reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 19 most recent posts we hold, published 22 July 2026 to 12 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
4
across the posts below
Posts paid on
1
of 19 we hold a reading for · 5%
Most on one post
4
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @How2AI. 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 19 most recent posts we hold for this entry, published 22 July 2026 to 12 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.
😈 xAI выпустила Grok Bot – интересная штука.
По сути – ИИ-агенты со своим собственным компьютером. Логинятся в Gmail, Salesforce, LinkedIn и практически любой сайт, работают 24/7 даже когда ваш ноутбук закрыт, и возвращаются только когда реально нужен человек.
Показал workflow один раз – бот превращает его в рутину. Несколько ботов работают параллельно, общаются между собой и передают таски.
Клиенты есть под macOS…
🫵 Сколько возможностей для увеличения аудитории ты упустил, потому что снимать - долго, монтировать - ещё дольше, а нанять контенмейкера - дорого?
Мы научим вас как сделать из ИИ агента полноценного контенмейкера, делающео это за вас и экономящего ваши деньги и время
⁉️ Как? Сегодня стартует наш новый поток «ИИ-агенты для создания контента» — 3-дневный живой интенсив, где вся эта рутина уезжает агенту:
— харнесс с…
📱 Нововости ИИ 156!
ИИ-агенты вышли из-под контроля! OpenAI, Anthropic и Kimi подтверждают новые "побеги" моделей. Релизы Seedance 2.5, Flux 3 video и новая волна регулирования ИИ Творчества
Туть - https://youtu.be/rR7c-Ar0DG0
А уже послезавтра стартует наш поток по ИИ Агентам для создания контента
@how2ai | Забустить канал | Внедряем ИИ в бизнес
📱 Новое на ютуб - препарируем Minimax H3
Веса выложены на Hugging Face, модель ставится локально в ComfyUI. Умеет text-to-video и image-to-video, работает с референсами персонажа, стиля и голоса, поддерживает 11 языков включая русский и выдаёт до 2K.
Туть - https://youtu.be/xhp6JXaamFQ?si=MwwCmcIwI857jKgm
@how2ai | Забустить канал | Внедряем ИИ в бизнес
🤯 Безлимитный ChatGPT для ВСЕХ!
Правда только на модели Luna – самой маленькой.
Но даже бесплатные и Go пользователи теперь полчают безлимитный доступ к интеллекту от OpenAI. Чудесно.
@how2ai | Забустить канал | Внедряем ИИ в бизнес
😈 OpenAI сделали прикольное демо GPT-Live для бёрдвотчинга - гуляете, слушаете, спрашиваете "что это поёт?", модель отвечает на лету без пауз.
Их новая разговорная модель действительно хороша – не прерывается "на подумать" потому что может параллельно слушать и отвечать в то время, как gpt-5,5 обарабывает предыдущий запрос и использует инструменты.
В Codex тоже работает шикарно - запускает новые сессии, дает задачи…
😐 У Hermes уйма обновлений. Называют "The Herald Release"
📶 Wake words: задаёшь любую фразу вроде "hey Hermes" - говоришь её вслух, и Hermes начинает слушать. Дальше говоришь запрос как есть и Hermes стримит ответ по фразам, не дожидаясь генерации целиком. Можно перебивать, разные wake words можно привязать к разным профилям.
📶 A2A v1.0: Hermes говорит с другими агентами по стандартному протоколу - находит их, став…
🌎 В новом 155-м выпуске новостей ИИ:
На этот раз Claude сбежала из песочницы, опенсорс Kimi K3, мощнейшие видеорелизы Seedance 2.5 и MiniMax H3
📱 Уже на канале - https://youtu.be/1AN9_7pcJNY
⚡️ Курс по ИИ-разработке+ИИ Агентам на нашей новой учебной платформе! Научитесь создавать, деплоить и монетизировать ИИ-продукты с нуля - https://t.me/how2ai_bot?start=dl-1785656356706
@how2ai | Забустить канал 💗
🫵 Показываю рабочий пайплайн для автоматизации создания рилсов и шортсов через Claude Code:
Генерация сценария, цифровой двойник, картинки/видео/музыка через Magnific, монтаж и motion-дизайн в HyperFrames и автоматическое создание проектов Premiere и DaVinci Resolve!
Очень плотный получился ролик и главное, что сам ролик я смонтировал с помощью техник про которые в нем же и рассказываю 🤪
Ролик уже на ютубе - https…
👀 HF выпустили подробный блог-пост и дашборд с визуализацией атаки ИИ-агента OpenAI.
В течение примерно двух с половиной дней внутри нашей инфраструктуры автономный ИИ-агент, работающий на основе комбинации моделей OpenAI, совершил сквозное вторжение на нашу платформу. Наша криминалистическая реконструкция охватывает около 17 600 действий злоумышленника, которые нам удалось восстановить.
Продуктивно OpenAI, продукт…
📚 А вы знали, что AI-компании массово уничтожают физические носители информации?
Они скупают старые и редкие книги... Сканируют содержимое для тренировки моделей... И перерабатывают оригиналы (да здравствует безотходное производство и нежелание тратить деньги на хранение "старого хлама")
Каждая отсканированная книга исчезает из физического мира навсегда. Знание остаётся ТОЛЬКО внутри системы, которую нельзя подержа…
Твиттерские как всегда отреагировали креативно.
Всех узнали? 😧
@how2ai | Забустить канал | Внедряем ИИ в бизнес
😁36🔥7👏3💯1
Signed дядя_д
Showing the 12 most recent of 19 posts we hold for @How2AI. 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
Citation-graph rank — 178,999 of 1,160,990entries 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 12 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 12 August 2026 — this
entry's latest reading, not the date you are reading this.
“How2AI” (@How2AI), 15,299 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/How2AI.
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.