3 measurements spanning 7 days, net +10. 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 837–850 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
13 Aug 2026, 10:05
848
+10
6 Aug 2026, 15:05
838
no change
6 Aug 2026, 08:19
838
first reading
Engagement
20 posts held, back to 4 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 1 pageof Telegram’s post history, 20 posts per page.
ERR · 30 days
64.1%
avg views ÷ 848 subscribers
Avg views / post
544
10 posts measured
Reaction rate
2.94%
reactions ÷ views · ER floor
Posts in window
10
of 20 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 4 August 2026
Posts held
20 (4 July 2026 – 4 August 2026)
Views total
5,435
Reactions total
160
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
6 Aug 2026, 15:05 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.
Reaction mix
310 reactions across 18 posts, in 11 distinct kinds. The most used accounts for 47.1% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👍
146
47.1%
❤
94
30.3%
🔥
37
11.9%
😁
16
5.16%
💯
9
2.90%
💊
2
0.645%
🤝
2
0.645%
🐳
1
0.323%
👌
1
0.323%
👏
1
0.323%
🤔
1
0.323%
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 20 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 310reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 4 July 2026 to 4 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
75
across the posts below
Posts paid on
12
of 20 we hold a reading for · 60%
Most on one post
44
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @businessaandtech. 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 20 most recent posts we hold for this entry, published 4 July 2026 to 4 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.
Эта картинка залетела у меня в LinkedIn, решил разместить и тут.
#заметки
Свежее исследование в Telematics and Informatics (2026) кластеризует страны ЕС по готовности к AI в госуслугах.
Первое: цифровые навыки граждан и то, как активно они пользуются е-услугами.
Второе: прозрачность государства и доступность электронных сервисов.
Получилось шесть кластеров.
Дания, Нидерланды, Финляндия впереди по обеим осям. Их…
В прошлый раз обещал:если тема с AI в фарме зайдёт, распишу отдельно, что происходит с лекарством после одобрения. Судя по комментариям, зашла. Держу слово.
#заметки
Короткое напоминание с прошлого раза. До пациента добирается меньше одного лекарства-кандидата из тысячи, и почти все потери происходят на испытаниях на людях. Кажется логичным, что если препарат такое пережил, дальше должно быть проще. В реальности не…
Я не медик и не фармацевт. Я всю жизнь работаю с бизнесом и технологиями. А это значит, что я целыми днями отделяю то, что технологии реально умеют, от того, что нам про них продают.
#заметки
И сильнее всего этот рефлекс спотыкается на медицине.
Мне стало интересно копнуть, что происходит в разработке лекарств и в фарме. Копнул, разобрался и решил разложить по-простому. Думаю, тема многим интересна, но времени вчи…
Читаю кейс Harvard Business School про французский стартап Whoz. Про то, как внутри компании случайно выросла вторая компания.
#заметки
Первоисточник тут, кому интересно: https://www.hbs.edu/faculty/Pages/item.aspx?num=68511
Whoz делает софт для стаффинга. Помогает понять, кто из консультантов сейчас свободен и кого куда поставить на проект. Обычный вертикальный SaaS, 800 тысяч пользователей, среди клиентов Capgem…
Блин, вчера забыл дайджест выложить. Ловите сегодня, с запасом на выходные.
#digest
———
ВЕНЧУРНЫЕ ПАРТНЁРЫ ИДУТ РАБОТАТЬ В СВОИ ЖЕ СТАРТАПЫ
Judith Dada, general partner берлинского Visionaries Club, в июне стала co-CEO портфельного ИИ-стартапа Langdock, оставшись при этом senior partner в фонде. Сам Visionaries недавно объявил переход на модель GP-led: инвестициями теперь занимаются два партнёра, Lacher и Kondrag…
#данные
Digital Evolution Index 2026 от Harvard Business Review и Digital Planet (Fletcher School, Tufts). 125 стран разложили по двум осям.
Первая, насколько страна сейчас цифровая.
Вторая, с какой скоростью она становится цифровой последние 17 лет. Картинка в посте.
Если у вас аутсорсинг или стартап и большая часть продаж идет в Германию, Нидерланды, Великобританию, Швецию,этот пост для вас.
Все четыре страны в…
Последние недели залип на тему дронов и dual-use
#заметки
Весной над Вильнюсом один залётный дрон закрыл небо: рейсы отменили, людей отправили в убежища. Я полез разбираться, что вообще происходит в индустрии, ну и втянулся.
Пару лет назад на полную автономию, когда дрон сам выбирает цель, многие махнули рукой. Обещали много, показывали мало, пахло очередной «зимой» ИИ: шума больше, чем толку. Наведение на последн…
Привет. Пятничный дайджест. Три истории, и на этой неделе они про одно: как AI входит в реальные компании и школы, и сколько вокруг этого трения.
#digest
———
КОДИНГ-АГЕНТ GROK ТИХО ЗАЛИВАЛ ЧУЖОЙ КОД ЦЕЛИКОМ НА СЕРВЕРЫ xAI
Исследователь по безопасности вскрыл Grok Build (это консольный AI-помощник для программистов от xAI, конкурент Claude Code и Cursor) и показал: инструмент молча отправлял весь твой репозиторий це…
США переживают крупнейший технологический строительный бум в современной истории.
При этом совокупные инвестиции в стране не растут. Звучит как противоречие, но верно и то и другое.
Вышел новый отчёт McKinsey Global Institute о глобальных инвестициях, давайте почитаем вместе.
#данные
Вложения в строительство дата-центров в США выросли на 200 процентов с момента запуска ChatGPT. Технологические инвестиции в целом …
Showing the 12 most recent of 20 posts we hold for @businessaandtech. 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 — 271,637 of 1,480,688entries 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.
Mentions
Named by 3 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 13 August 2026 — this
entry's latest reading, not the date you are reading this.
“Переводчик с технического | Roman Rimsha” (@businessaandtech), 848 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/businessaandtech.
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.