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 75% 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
34 measurements spanning 43 days, net +383. 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 11,983–12,480 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 34
Measured (UTC)
Subscribers
Change
18 Sept 2026, 22:59
12,423
+17
16 Sept 2026, 15:41
12,406
+1
14 Sept 2026, 19:39
12,405
-12
13 Sept 2026, 08:55
12,417
-1
11 Sept 2026, 10:37
12,418
-2
8 Sept 2026, 16:41
12,420
+14
5 Sept 2026, 12:58
12,406
+6
3 Sept 2026, 14:56
12,400
+13
2 Sept 2026, 07:34
12,387
+31
1 Sept 2026, 06:48
12,356
+6
31 Aug 2026, 08:37
12,350
+59
30 Aug 2026, 08:54
12,291
+6
29 Aug 2026, 12:03
12,285
+25
28 Aug 2026, 13:46
12,260
+34
27 Aug 2026, 14:04
12,226
+23
26 Aug 2026, 17:07
12,203
+32
25 Aug 2026, 17:37
12,171
+7
24 Aug 2026, 15:14
12,164
+3
23 Aug 2026, 00:55
12,161
-1
21 Aug 2026, 14:44
12,162
first reading
Engagement
48 posts held, back to 1 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 49 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
4.77%
avg views ÷ 12,423 subscribers
Avg views / post
592
13 posts measured
Reaction rate
1.60%
reactions ÷ views · ER floor
Posts in window
14
of 48 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
48 (1 August 2026 – 2 September 2026)
Views total
7,696
Reactions total
123
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
2 Sept 2026, 22:05 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
13m 10s
Average length
1m 28s
Measured directly from 9 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
449 reactions across 46 posts, in 12 distinct kinds. The most used accounts for 48.6% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
218
48.6%
🔥
143
31.8%
👍
35
7.80%
⚡
16
3.56%
👏
10
2.23%
😍
9
2.00%
💯
5
1.11%
🙏
5
1.11%
🤩
4
0.891%
😎
2
0.445%
😱
1
0.223%
🤯
1
0.223%
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 46 of the 48 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 449 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 48 most recent posts we hold, published 1 August 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.
1 ДЕНЬ ДО ВОРКШОПА ПО ЛЕНИВЫМ REELS ⏰
Завтра в 18:00 мск – проведу для вас бесплатный воркшоп по ленивым рилзам!
Сразу скажу, повтор делать не будем. Это не классический вебинар, а именно формат воркшопа.
Мы в прямом эфире с Василисой Болотовой (эксперт клуба по нейросетям) показываем вам пошагово, что делать. А вы берёте и повторяете 🔥
Что будет на воркшопе?
– Получите 30+ готовых сценариев Reels для своего б…
ТРЕНД №1 – ЛЕНИВЫЕ REELS
173 000+ просмотров за полчаса 😍
Забудьте уже о сложном монтаже.
Это антитренд!
Сейчас в тренде – ленивые рилзы.
В августе я прошла зарубежное обучение по маркетингу от Meta (признана экстремистской и запрещена в РФ). Именно этой корпорации принадлежит Нельзяграм.
Из инсайтов:
1. Алгоритмы не ищут идеальный контент. Они ищут признаки жизни, регулярность и повторяемость. Для них это сигна…
ШТАБ-КВАРТИРА Reels 😍🔥
Монтируем ролики через нейронки за 5 минут
Мы в клубе по нейросетям нашли самый эффективный способ монтировать видео! Назвали его «Ленивые рилзы»
Вам больше не придётся тратиться на монтажеров и сидеть по 2-3 часа в монтажных программах.
Да даже себя снимать необязательно! Весь процесс от вирусного инфоповода до готового ролика на нейронке.
За полчаса вы сможете монтировать себе по 7-10 Ree…
ТОП-18 КОМАНД ДЛЯ ИЗОБРАЖЕНИЙ 😍
Просто загружаете своё изображение в ChatGPT и даёте ему любую команду:
/crosssection – товар в разрезе, видно что внутри
/ingredients – состав товара разложен рядом с упаковкой
/blueprint – товар как инженерный чертёж на синей сетке
/billboard – товар на 3D-рекламном билборде в городе
/creativeads – готовый рекламный креатив с товаром
/premiumshowcase – товар в пре…
🔥 3 СЕНТЯБРЯ | ЖИВОЙ ВОРКШОП ПО НЕЙРОСЕТЯМ
«Создай 30+ сценариев Reels в нейросетях за 60 минут, даже если у тебя нет ни одной идеи»
📅 3 сентября
⏰ 18:00 мск
Без регистрации, бесплатно
Новаторы, вы приглашены на закрытый воркшоп клуба по нейросетям!
Хочу показать вам, чем мы занимаемся в клубе. Вместе с экспертом Василисой (8 лет в AI) проведем бесплатный воркшоп для тех, кто хочет делегировать весь контент нейро…
ОСТАЛИСЬ СУТКИ ⏰
Все материалы и уроки сгорают в 23:59 мск!
Новаторы, идеальный момент вступить в клуб нейросетей сегодня до 23:59 мск.
1. Во-первых, вы сохраните себе доступ ко ВСЕМ материалам августа:
• Настроите ИИ-дайджест вирусных инфоповодов на каждый день
• Делегируете создание вирусных каруселей и сценариев для Reels
• Создадите ШТАБ-продукта и разработаете продуктовую линейку
• Научитесь делать презентаци…
📖📖📖📖
Вирусные карусели с Claude (7 минут!)
Эксперт нашего клуба по нейросетям Василиса записала для вас пошаговый план, как создать карусель в нейронке 🤩
Вы научитесь правильно формулировать запросы для Claude и быстро генерировать:
– структуру карусели
– цепляющие заголовки
– сильные офферы
– логичную подачу слайдов
А ещё увидите, как переносить карусели из Claude прямиком в Canva и редактировать всё, что вы зах…
ПРОМПТ
Как создать лид-магнит, который генерит трафик и продажи
Эффективный маркетинг в соцсетях без лид-магнита уже сложно представить.
Это та самая точка захвата, которая превращает случайного зрителя Reels в подписчика, а потом и в клиента 🔥
Промпт:
Ты – маркетолог, который создаёт лид-магниты, реально конвертирующие в продажи.
Придумай 10 идей лид-магнитов для [продукт/ниша]. Изучи рынок и потребности целевой …
📌📌📌📌📌📌📌
Инструкции, шаблоны, промпты, после которых ваш блог начнёт расти ⤵️
Собрала для вас всё, что вы должны прочитать в этом канале.
– 30 расширений для Claude, которые заменят целую команду [забрать]
– 70+ трендовых инфоповодов в вашей нише на каждый день [повторить здесь]
– 7 промптов от отдела продаж для высоких конверсий [сохранить тут]
– Промпт-конструктор для контента [забрать]
– Как сделать продающий са…
ЗАКРЫТЫЙ КЛУБ по НЕЙРОСЕТЯМ: для кого он? Что внутри? Как в него попасть? Сколько это стоит?💰
Хочу познакомиться с новенькими)
Меня зовут Юлия Родочинская, маркетолог и собственник бренда косметики JCos ❤️
В маркетинге я уже 18 лет, девять из которых развиваю свою онлайн-школу. За это время обучила 70 000+ студентов маркетингу и нейронкам по всему миру.
В этом году я создала Нейроклуб, где в живом формате мы обуч…
30 РАСШИРЕНИЙ ДЛЯ CLAUDE, чтобы выжать максимум из нейронки
Сейчас докажу, что вы пользуетесь только 5% того, что реально умеют нейронки 🤯
Есть штука под названием «расширения». Звучит по-айтишному, но смысл простой: это как подключить к Claude дизайнера, маркетолога, копирайтера, методолога, программиста, личного бизнес-ассистента.
Вот что может делать Claude с помощью расширений вместо вас:
– собирает дизайн в …
❤7🔥3⚡2
Showing the 12 most recent of 48 posts we hold for @neurobiznes. 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.
Posts edited after publishing
@neurobiznes edited 1 post after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
First edit seen
27 August 2026
Most recent edit
27 August 2026
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 18 September 2026 — this
entry's latest reading, not the date you are reading this.
“Родочинская о нейросетях” (@neurobiznes), 12,423 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/neurobiznes.
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.