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 89% 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
16 measurements spanning 39 days, net -1,321. 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 7,069–10,719 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
15 Sept 2026, 18:56
8,977
-89
11 Sept 2026, 18:56
9,066
-249
7 Sept 2026, 03:58
9,315
-515
2 Sept 2026, 06:23
9,830
+2,340
30 Aug 2026, 16:05
7,490
-241
27 Aug 2026, 17:57
7,731
-1,237
25 Aug 2026, 00:44
8,968
-314
21 Aug 2026, 20:17
9,282
-80
18 Aug 2026, 10:52
9,362
-131
15 Aug 2026, 00:55
9,493
-306
11 Aug 2026, 13:43
9,799
-385
10 Aug 2026, 16:02
10,184
-77
9 Aug 2026, 12:38
10,261
-21
8 Aug 2026, 12:33
10,282
-16
7 Aug 2026, 13:16
10,298
no change
7 Aug 2026, 13:08
10,298
first reading
Engagement
27 posts held, back to 26 May 2026 — the reader has reached the start of this channel’s public history, so this is the full archive Telegram still exposes. Read across 33 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
1.48%
avg views ÷ 8,977 subscribers
Avg views / post
133
2 posts measured
Reaction rate
6.42%
reactions ÷ views · ER floor
Posts in window
2
of 27 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
27 (26 May 2026 – 26 August 2026)
Views total
265
Reactions total
17
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
28 Aug 2026, 20:47 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
44s
Average length
22s
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.
Reaction mix
249 reactions across 25 posts, in 15 distinct kinds. The most used accounts for 35.3% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👍
88
35.3%
❤
35
14.1%
💯
32
12.9%
❤🔥
22
8.84%
🔥
22
8.84%
🤝
18
7.23%
👏
11
4.42%
🙏
7
2.81%
🍾
6
2.41%
👀
2
0.803%
😐
2
0.803%
🏆
1
0.402%
🕊
1
0.402%
🤔
1
0.402%
🥰
1
0.402%
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 25 of the 27 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 249 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 27 most recent posts we hold, published 26 May 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
33
across the posts below
Posts paid on
20
of 27 we hold a reading for · 74%
Most on one post
11
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @RUcofounder. 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 27 most recent posts we hold for this entry, published 26 May 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.
Сегодня команда «Выбирай свое» выступила на XIII Международном форуме технологического развития «Технопром» в Новосибирске.
Представили нашу платформу «Цифровое просвещение» и новый этап развития Всероссийского научно-технологического диктанта, который в этом году проходит по теме «Человек и космос».
Но наша задача шире, чем просто провести диктант онлайн.
Мы строим единое цифровое пространство, которое должно соп…
С.И. Морозов в недавнем посте отметил, что промышленное развитие страны начинается с личности — с профессионализма, ответственности, умения вести за собой и верности своему делу.
Именно поэтому мы активно работали над созданием платформы 🇷🇺 Цифровое просвещение, где молодые люди смогут определить траекторию профессионального развития, накапливать и укреплять необходимые навыки, а также принимать участие в мероприяти…
Всероссийский научно-технологический диктант набирает обороты и расширяет карту участников — к приглашению присоединяются студенты различных ВУЗов.
Регистрация уже доступна: https://dictant.tech/register.
А 22 октября 2026 года можно будет пройти диктант очно или подключиться онлайн из любого региона России.
Кстати, презентация проекта состоится уже 26 августа на топ-сессии Технопрома 2026 в Новосибирске!
На днях выступил на форуме «Венчурный ландшафт 2026», где вместе с представителями бизнеса, инвесторов и юристов обсуждали интеллектуальную собственность как инвестиционный актив.
Отдельно предложил Московскому инновационному кластеру сделать IP-паспорт технологического проекта - понятный стандартизированный документ, который показывает инвестору, что именно у проекта есть с точки зрения интеллектуальной собственнос…
22 октября стартует Всероссийский научно-технологический диктант — федеральный проект, проводящийся в рамках российского десятилетия науки и технологий.
Для нас это стало особенным вызовом - модернизировать Диктант, сделать его более технологичным и выйти далеко за рамки одного мероприятия. Поэтому в 2026 году Диктант пройдёт на базе онлайн-платфомы 🇷🇺 Цифровое просвещение.
Платформа стала результатом труда эксперт…
Венчурный ландшафт 2026
13 августа в Москве пройдет юбилейный инвестиционный форум от Московского венчурного фонда!
В этом году по приглашению AG-LEGAL выступлю спикером в самой интересной сессии:
"Интеллектуальная собственность как инвестиционный актив"
Коллеги собрали крутых спикеров, чтобы честно поговорить, что думают бизнес, инвесторы и юристы об интеллектуальной собственности в эпоху ИИ, импортозамещения и …
В 2019 году РАНХиГС выпустила доклад «Государство как платформа: люди и технологии». Перечитал его сейчас, спустя семь лет, некоторые тезисы выглядят даже актуальнее, чем тогда.
Главная идея проста: цифровизация государства - это не перевод справок и заявлений из бумаги в электронную форму. Это изменение самой модели государственного управления.
Авторы еще тогда писали о переходе от «данных и документов» к управлен…
Бойназаров Комрон, студент МГСУ, приглашает студентов и всех молодых людей принять участие в IV Всероссийском научно-технологическом диктанте, https://dictant.tech/
Все регистрируемся!
Дорогие друзья! Последние месяцы я с горечью наблюдаю, как тематика малых технологических компаний постепенно исчезает из числа приоритетов профильных ведомств. Государственное внимание к развитию МТК сегодня объективно недостаточно, а многие инициативы, которые еще недавно активно обсуждались, фактически остановились.
Но именно малые технологические компании создают новые продукты, рабочие места, обеспечивают технол…
📈 Вклад малых технологических компаний в добавленную стоимость высокотеха вырос вдвое за два года.
🔎 Совместное исследование Фонда «Сколково» и АНО «Центр технологических инициатив Сколково» и при поддержке Минэкономразвития России показало: вклад МТК в валовую добавленную стоимость высокотехнологичного сектора достиг 1,57% — почти вдвое больше, чем два года назад. Совокупная выручка сектора — 1,4 трлн рублей.
В ре…
⚡️ Главный вывод нового исследования рынка ИИ в России — эпоха хайпа закончилась. Началась эпоха обоснований и выгоды.
Исследование Apple Hills Digital показывает, что российский рынок ПО с искусственным интеллектом в 2025 году достиг 25 млрд рублей, увеличившись на 27% по сравнению с предыдущим годом. При этом уже сегодня компании переходят от экспериментов к промышленному внедрению ИИ в конкретные бизнес-процессы.…
У России нет шансов? С такой логикой их действительно не будет.
На днях Наталья Касперская заявила, что Россия не сможет догнать США и Китай в разработке больших фундаментальных моделей искусственного интеллекта. По её словам, мы «идём пешком по тем же рельсам, по которым едут поезда», а для создания конкурентоспособных моделей необходимы миллиарды долларов и колоссальные вычислительные ресурсы.
Если цитата передан…
👍6💯5❤2👏2🤔1
Showing the 12 most recent of 27 posts we hold for @RUcofounder. 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.
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 15 September 2026 — this
entry's latest reading, not the date you are reading this.
“Сооснователь” (@RUcofounder), 8,977 subscribers as measured 15 September 2026. Telegram Register, tgregister.com/channel/RUcofounder.
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.