Channel
@cogmodel
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
1,770subscribers
-1 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
| Telegram ID | -1001124306846 |
|---|---|
| Type | Channel |
| Username | @cogmodel |
| Created | Between 1 June 2017 and 31 October 2020— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 23 August 2026 |
| Measurements held | 5 |
| Confirmed unchanged | 1 time, most recently 23 August 2026 |
| On Telegram | t.me/cogmodel |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 23 Aug 2026, 21:48 | 1,770 | -3 |
| 19 Aug 2026, 20:23 | 1,773 | +1 |
| 13 Aug 2026, 03:26 | 1,772 | +1 |
| 6 Aug 2026, 16:32 | 1,771 | no change |
| 6 Aug 2026, 14:35 | 1,771 | first reading |
9 posts held, back to 11 June 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 2 pagesof 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 9 posts for this entry, the most recent from 24 July 2026. An engagement rate over an empty window would be a number about nothing.
Measured directly from 1 video 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.
134 reactions across 9 posts, in 5 distinct kinds. The most used accounts for 56.7% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 🔥 | 76 | 56.7% | |
| ❤ | 49 | 36.6% | |
| 👏 | 6 | 4.48% | |
| ❤🔥 | 2 | 1.49% | |
| 👍 | 1 | 0.746% |
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 9 of the 9 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 134reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 9 most recent posts we hold, published 11 June 2026 to 24 July 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.
🦾 — Запускаем дополнительный набор в магистратуру ФПМИ МФТИ по искусственному интеллекту и робототехнике! Поступление проходит по 2 направлениям: — “Фундаментальные методы искусственного интеллекта” – база ЦКМ, 25 мест — “Мультимодальный искусственный интеллект”– база Институт AIRI, 10 мест Для поступления необходимо: 🪼Заполнить заявку на нашем в форме до 12:00 28 июля и пройти собеседование в Центре. 🪼Подать докум…
🔥9
🪼TerraCognitaSLAM: проект нашего сотрудника на инвестиционной программе. Наш сотрудник Олег Буличев защитил свой проект TerraCognitaSLAM на программе Трансляционных Исследований от Центрального Университета. Проект родился благодаря участию Олега в археологическом конкурсе — он увидел пробел в технологиях и решил его закрыть. TerraCognitaSLAM — это система навигации для роботов там, где GPS не работает: под кронами…
🔥24❤9👏6👍1
🪼Дайджест ЦКМ: начинаем неделю с полезных материалов Собрали для вас подборку свежих статей и разработок — от генерации 3D-сцен до новых подходов к вниманию в нейросетях и организации научного поиска. 3D и Генерация сцен Метод Sage от команды NVIDIA — генерацию интерактивных 3D-сцен с помощью LLM/VLM тул-коллинга на базе Open3D (ранее упоминался как QUEN3-VL). В отличие от статичных мешей, объекты загружаются в Isa…
❤11
💫Сотрудники и студенты из команды ЦКМ и Института AIRI на ICML 2026! На этой неделе в Сеуле прошла ICML 2026 — одна из сильнейших мировых конференций в области машинного обучения (категория А*). KAGE-Bench: Fast Known-Axis Visual Generalization Evaluation for Reinforcement Learning — бенчмарк для быстрой и прозрачной оценки того, как алгоритмы обучения с подкреплением обобщают визуальные признаки по заданным осям (…
🔥23❤9
🎓 — Семинар 21. Защита магистерских диссертаций выпускников ЦКМ 2026 Ещё одна группа морских котиков ИИ готова к финальной миссии своего обучения — защите магистерской работы🏆 За два года мы постарались передать студентам самые актуальные и прикладные знания в области ИИ и робототехники, а ребята достигли больших успехов. Приглашаем всех присоединиться и послушать выступления! 📹 Трансляция ВК #семинары #магистрат
❤8
💫 — Начинаем семинар, присоединяйтесь к трансляции в ВК или на YouTube!
🔥4
🎓 — Семинар 20. Обзор конференции ICRA 2026 | Александр Панов, Дмитрий Юдин, Дмитрий Макаров, Юлия Даник В начале июня наша команда выезжала в Вену на ICRA 2026. Это крупнейшая в мире конференция по робототехнике и автоматизации. На конференцию прошло 3 наших статьи: 1) Dynamic Neural Potential Field: Online Trajectory Optimization in Presence of Moving Obstacles — представляет метод нейросетевой генерации траектор…
🔥9❤3
💫 — Начинаем семинар, присоединяйтесь к трансляции в ВК или на YouTube!
🔥2
⚡️ — Робототехника в археологии — рассказываем о ходе соревнований Экспедиция.Земля, трек Археология. Конкурс предполагает разработку наземных мобильных роботов, позволяющих с высокой точностью обнаруживать и классифицировать археологические объекты и предметы различного состава, расположенных на различной глубине под землей. Наша команда под руководством Олега Буличева уже участвовала в соревнованиях в прошлом год…
❤9🔥5❤🔥2
Showing the 9 most recent of 9 posts we hold for @cogmodel. 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 — 189,551 of 1,585,381entries 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.
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.
Named by 4 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.
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.
“Center for Cognitive Modeling” (@cogmodel), 1,770 subscribers as measured 23 August 2026. Telegram Register, tgregister.com/channel/cogmodel.
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.