Channel
@linza_app
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
67subscribers
-3 since we began measuring on 9 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1002427599373 |
|---|---|
| Type | Channel |
| Username | @linza_app |
| Created | Between 1 September 2024 and 31 March 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 10 August 2026 |
| Last confirmed live | 31 August 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 2 times, most recently 31 August 2026 |
| On Telegram | t.me/linza_app |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 23 Aug 2026, 18:19 | 67 | -3 |
| 10 Aug 2026, 00:01 | 70 | no change |
| 9 Aug 2026, 06:47 | 70 | first reading |
7 posts held, back to 9 October 2025 — 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 page of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 7 posts for this entry, the most recent from 15 May 2026. An engagement rate over an empty window would be a number about nothing.
Measured directly from 3 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.
20 reactions across 5 posts, in 6 distinct kinds. The most used accounts for 40.0% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 8 | 40.0% | |
| 👍 | 4 | 20.0% | |
| 🔥 | 3 | 15.0% | |
| 💯 | 2 | 10.0% | |
| 😱 | 2 | 10.0% | |
| 👌 | 1 | 5.00% |
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 5 of the 7 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 20 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 7 most recent posts we hold, published 9 October 2025 to 15 May 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.
Уже кажется бесконечным спор о дипфейках и технологиях. Надеюсь, запрещать фотошоп, искусственный интеллект, наложение театральных масок не будут 😉 Соцсетям могут предложить самостоятельно бороться с дипфейками Главный радиочастотный центр Роскомнадзора (ГРЧЦ) предлагает соцсетям самим превентивно выявлять и блокировать резонансные дипфейки до проверки достоверности информации. Участники рынка отмечают, что техничес…
💯2
🟣 МИТ — Мы ИТ на Московском инновационном юридическом форуме «Право для лидерства» 14–15 мая 2026 года Ассоциация МИТ — Мы ИТ приняла участие в крупнейшем юридическом событии страны — МИЮФ-2026. ✍🏻 Два стратегических соглашения В рамках форума подписаны соглашения о сотрудничестве: ▪️ между Ассоциацией МИТ — Мы ИТ и Московским государственным юридическим университетом имени О. Е. Кутафина (МГЮА) о стратегическом пар…
❤4🔥1
Обсудили на CSTB изменения регуляторики и тренды автоматизации комплаенса с помощью ИИ. Почитать презентацию можно тут На практике бывает трудно понять, как отличить степень интимности мужских рукопожатий, является ли контент запрещенным или только требует маркировки. Давайте разбираться вместе 😉 - Наталия Тылевич, генеральный директор ООО «Социальная лаборатория», продукт LINZA DETECTOR - выявление деструктивного …
👍3👌1
Наконец-то эта история закончилась и все официально. А фактически это важный сигнал. Решение суда показывает разрыв между фактической экономикой ИТ-проектов и стандартами судебного доказывания: при недостатке формализованных документов даже очевидные для бизнеса обстоятельства могут остаться недоказанными. При этом процессуально такие споры требуют серьёзных юридических ресурсов и несут риск значительных судебных изд…
😱2
http://www.kremlin.ru/acts/assignments/orders/76076
⏭А мы делимся новым интервью⏮ 🔸Наталия Тылевич, CEO Social Lab, руководитель комитета экономики рынка данных и ИИ МИТ-Мы ИТ, рассказала, как СмартСтаффинг и НейроСтайффинг меняют подходы к работе и оптимизируют процессы в компаниях. 💡 Также она поделилась своими впечатлениями от круглого стола «СмартСтаффинг и НейроСтаффинг – трансформация труда». ➡️ Полное интервью смотрите в нашем видео, а также на площадках Вко…
❤4🔥2👍1
Photo, posted without a caption
Showing the 7 most recent of 7 posts we hold for @linza_app. 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.
Republishes
Channels on the register whose posts this channel has forwarded.
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.
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.
Names
Channels on the register whose handles appear in this channel's posts.
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.
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 23 August 2026 — this entry's latest reading, not the date you are reading this.
“Наталия Тылевич: ИИ и реальность 😉” (@linza_app), 67 subscribers as measured 23 August 2026. Telegram Register, tgregister.com/channel/linza_app.
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.