Channel
@omutai
On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry
509subscribers
+4 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1002170921330 |
|---|---|
| Type | Channel |
| Username | @omutai |
| Created | 16 July 2024 — measured — dated from the channel’s first post |
| First recorded | 6 August 2026 |
| Last confirmed live | 4 September 2026 |
| Measurements held | 6 |
| Confirmed unchanged | 1 time, most recently 4 September 2026 |
| On Telegram | t.me/omutai |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 4 Sept 2026, 04:17 | 509 | +1 |
| 28 Aug 2026, 13:15 | 508 | -1 |
| 21 Aug 2026, 13:09 | 509 | +3 |
| 15 Aug 2026, 01:34 | 506 | +1 |
| 6 Aug 2026, 19:01 | 505 | no change |
| 6 Aug 2026, 18:49 | 505 | first reading |
5 posts held, back to 16 July 2024 — 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 5 posts for this entry, the most recent from 15 November 2024. An engagement rate over an empty window would be a number about nothing.
147 reactions across 4 posts, in 13 distinct kinds. The most used accounts for 40.1% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 🔥 | 59 | 40.1% | |
| ❤ | 41 | 27.9% | |
| ❤🔥 | 14 | 9.52% | |
| 👍 | 9 | 6.12% | |
| 🤓 | 7 | 4.76% | |
| 🤯 | 6 | 4.08% | |
| 🐳 | 4 | 2.72% | |
| 🎉 | 2 | 1.36% | |
| 🍓 | 1 | 0.68% | |
| 👏 | 1 | 0.68% | |
| 💯 | 1 | 0.68% | |
| 😁 | 1 | 0.68% | |
| 🥴 | 1 | 0.68% |
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 4 of the 5 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 147 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 5 most recent posts we hold, published 16 July 2024 to 15 November 2024, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Лаборатория 🔤🔤🔤🔤 🅰️🔤 (T-Bank AI Research и Центральный университет) набирает студентов для написания курсовых/дипломов и совместных исследований по нескольким направлениям: LLM Foundations - Адаптивные вычисления в LLM - Разработка эффективных архитектур (SSM etc.) - Интерпретируемость языковых моделей (Sparse Autoencoders, Sparse Crosscoders etc.) LLM Alignment - Исследование offline методов алайнмента - Новые ви…
🔥34👍6❤3
Мы придумали новый метод SAE Match, который помогает сопоставлять понятные фичи, выделенные Sparse Autoencoder (SAE), между разными слоями LLM. Это важный шаг к тому, чтобы разобраться, как LLM обрабатывают информацию, показывая, как фичи сохраняются или меняются, пока данные проходят через модель. Одна из ключевых частей нашего метода — это техника "parameter folding", где мы напрямую включаем пороги активации в ве…
🔥18❤8👍2
Прямо сейчас идет ICML 2024, а на нем опубликована статья Славы Синего (@ummagumm_a) в коллабе с друзьями из AIRI – In-Context Reinforcement Learning for Variable Action Spaces! В этой статье писали о новом методе In-Context RL, способном использовать из контекста действия произвольной природы. А самое главное, может даже меняться число действий, которые может сделать агент. Сейчас Слава работает в Omut AI над мето…
❤🔥14🔥7🐳4👍1💯1
Всем привет, мы команда Omut AI! Вы уже можете нас знать как Research команду Т-Банка, а теперь мы запускаем совместную лабораторию с Центральным Университетом. Будем работать над образованием в ЦУ, а у студентов также будет прямой доступ к нам, чтобы разбираться в AI вместе. Здесь мы продолжим заниматься исследованиями AI, направленными на улучшение методов в трех направлениях: 🅾️ AI Alignment – создание AI, согл…
❤30🤓7🤯6🎉2🍓1👏1🥴1😁1
Channel created
Showing the 5 most recent of 5 posts we hold for @omutai. 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.
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.
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 4 September 2026 — this entry's latest reading, not the date you are reading this.
“Omut AI” (@omutai), 509 subscribers as measured 4 September 2026. Telegram Register, tgregister.com/channel/omutai.
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.