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Channel

Жёлтый AI

@zheltyi_ai

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry

9,387subscribers

+48 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1001373379552
TypeChannel
Username@zheltyi_ai
CreatedBetween 1 April 2018 and 31 August 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live16 September 2026
Measurements held14
Confirmed unchanged1 time, most recently 16 September 2026
On Telegramt.me/zheltyi_ai

Topic

Technology — 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 100% 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

9,3399,3959,3676 August 2026 — 9,339 subscribers6 August 2026 — 9,340 subscribers9 August 2026 — 9,346 subscribers12 August 2026 — 9,367 subscribers16 August 2026 — 9,383 subscribers19 August 2026 — 9,391 subscribers22 August 2026 — 9,392 subscribers25 August 2026 — 9,395 subscribers28 August 2026 — 9,386 subscribers31 August 2026 — 9,387 subscribers4 September 2026 — 9,388 subscribers9 September 2026 — 9,391 subscribers12 September 2026 — 9,394 subscribers16 September 2026 — 9,387 subscribers9,3876 August 202616 September 2026
14 measurements spanning 41 days, net +48. 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 9,331–9,403 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
16 Sept 2026, 12:399,387-7
12 Sept 2026, 19:179,394+3
9 Sept 2026, 01:219,391+3
4 Sept 2026, 01:159,388+1
31 Aug 2026, 18:549,387+1
28 Aug 2026, 14:479,386-9
25 Aug 2026, 22:029,395+3
22 Aug 2026, 13:559,392+1
19 Aug 2026, 02:579,391+8
16 Aug 2026, 08:379,383+16
12 Aug 2026, 12:449,367+21
9 Aug 2026, 15:129,346+6
6 Aug 2026, 19:009,340+1
6 Aug 2026, 11:229,339first reading

Engagement

17 posts held, back to 12 November 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 32 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
18.6%
avg views ÷ 9,387 subscribers
Avg views / post
1,750
1 post measured
Reaction rate
2.80%
reactions ÷ views · ER floor
Posts in window
1
of 17 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
WindowRolling 30 days · latest post in window 27 August 2026
Posts held17 (12 November 2025 – 27 August 2026)
Views total1,750
Reactions total49
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken29 Aug 2026, 06:41 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
4s
Average length
4s

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.

Reaction mix

813 reactions across 17 posts, in 19 distinct kinds. The most used accounts for 34.8% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥28334.8%
❤12615.5%
👍819.96%
❤‍🔥637.75%
🥰536.52%
⚡506.15%
🤣475.78%
🥴283.44%
🏆192.34%
😍172.09%
🎉161.97%
😁91.11%
🐳60.738%
🙏40.492%
🤯40.492%
👏30.369%
👌20.246%
🌚10.123%
💯10.123%

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 17 of the 17 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 813 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 17 most recent posts we hold, published 12 November 2025 to 27 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.

Recent posts

27 Aug 2026, 13:35 UTC≈1,750 views49 reactionsread 29 August 2026

19 сентября наши спикеры выступят на Practical ML Conf 😎 — В 14:50 Даниил Гаврилов поучаствует в дискуссии о том, как исследования превращаются в продукты, почему иногда продукт появляется раньше статьи и какие результаты компании предпочитают вообще не публиковать. — В 15:30 Даниил Цимерман обсудит, где AI-агенты уже приносят измеримую пользу, а где пока остаются красивыми демками. — В 17:50 в зале «Код» Александ…

🔥17👍14🤣9⚡5❤4

21 Jul 2026, 12:10 UTC≈4,380 views65 reactionsread 29 August 2026
Photo

⚡️Делимся двумя релизами, о которых рассказывали на Turbo ML Conf T-Search — открытый агент-ретривер для сложного многошагового поиска. Это специализированная модель на основе Qwen3-35B-A3B. Она не генерирует ответ, а за несколько шагов находит нужные фрагменты в документах. Попробовать модель в деле можно на Hugging Face, а почитать, как мы обучали агента многошаговому поиску — в статье на Хабре. Perseus — открыты…

🔥34👍15⚡13❤‍🔥2❤1

2 Jul 2026, 13:48 UTC≈5,370 views4 reactionsread 29 August 2026
Sticker

Sticker, posted without a caption

🐳4

2 Jul 2026, 13:47 UTC≈5,370 views33 reactionsread 29 August 2026
Photo

✨ Пока ждем Turbo ML Conf предлагаем поиграть в мини-игру @LossMonkeyBot Всем же приятно смотреть как лосс падает? Пока fable делает вашу работу, можно вкатиться в макакинг 🦍 3 человека, которые попадут в начало лидерборда, заберут лего-банкоматы Т-Банк. Победителей объявим в комментариях 17 июля - за день до конференции!

🔥14🥴11❤5⚡2👌1

22 Jun 2026, 09:20 UTC≈5,630 views25 reactionsread 29 August 2026
Photo

Владивосток, мы знаем, чем вы займетесь 27 июня 👀 Встречаемся на T-Meetup: R&D! Нас ждут доклады, полезные знакомства и общение с топами индустрии. В программе 3 доклада: → «Почему существуют задачи, которые нельзя решить обычной разработкой?» — Станислав Моисеев Поговорим, где проходит граница между разработкой и R&D, почему некоторые технологические вызовы невозможно решить стандартными инженерными подходами и з…

👍12🔥9🏆4

16 Jun 2026, 12:28 UTC≈5,210 views104 reactionsread 29 August 2026
Photo

Получили ранний доступ к секретной модели Mistral: Le Gros Chaton — 30 трлн параметров, 256 тысяч экспертов. Подняли инференс на всём кластере, неделя прогрева — пока что сгенерировали только 10 токенов. Но это лучшие 10 токенов в нашей жизни. Правда, они пока только на французском. Так что начинаем обучение «Большой ко-Т».

🥰48🤣35🥴14🤯4🏆1👌1👍1

10 Jun 2026, 11:03 UTC≈7,100 views38 reactionsread 29 August 2026
Photo

⚡️ Открываем регистрацию на Turbo ML Conf 2026! Соберемся, чтобы обсудить глубокие исследования, прикладной ML и инженерные системы. В программе три трека. ✨ Fundamental Advances & Exploratory R&D Поговорим об архитектуре и обучении современных моделей, их интерпретируемости, безопасном поведении и способности к рассуждению и самокоррекции. ✨ Applied ML at Scale & Business Impact Рассмотрим внедрение ML в продукт…

🔥16❤15⚡5😁2

2 Jun 2026, 12:03 UTC≈6,000 views68 reactionsread 29 August 2026
Photo

Съездили в 🔤🔤🔤🔤🔤🔤 на AAMAS 2026, где у нас был oral с работой Enhancing Vision-Language Model Training with Reinforcement Learning in Synthetic Worlds for Real-World Success. В статье мы обучаем VLM-агентов через RL в дешевых синтетических средах: MiniWorld, Gym-Cards, ALFWorld и WebShop. Основная идея — если хотим, чтобы модель не просто красиво описывала картинку, а умела смотреть на состояние мира и делать послед…

❤27🔥21⚡12🤣3😁3🥴2

21 May 2026, 11:00 UTC≈6,060 views36 reactionsread 29 August 2026
Photo

⚡️ Turbo ML Conf возвращается! Бронируем ваше 18 июля, чтобы обсудить тренды, кейсы и технологии в ML. В этом году помимо докладов у нас будут представлены демозоны с разными ML-решениями. Вы сможете представить продукт или платформу вашей компании, основанную на ML-технологиях. Если вам есть что показать — оставляйте заявку на сайте. Мы особенно заинтересованы в опыте использования CV, RecSys и NLP. Всем участник…

👍14⚡12❤5❤‍🔥4🐳1

7 Apr 2026, 13:02 UTC≈7,460 views19 reactionsread 29 August 2026
Photo

Как эффективно объединить машинное обучение, разработку и эксплуатацию в устойчивую и масштабируемую систему? Обсудим на T-Meetup: MLOps в Нижнем Новгороде уже 9 апреля! Что будет в программе? → «Когда Kubernetes не справляется: как мы научили кластер жить под сильной батчевой нагрузкой» — Андрей Фунтиков Узнаем, как инфраструктурная команда ML Core прошла путь от регулярных падений под нагрузкой до уверенной рабо…

❤14🔥5

15 Mar 2026, 15:15 UTC≈7,680 views19 reactionsread 29 August 2026

Приглашаем всех на хакатон BitGN PAC1 🚀 11 апреля в офисе на Свердловской набережной, 44с2, пройдет финальный день международного соревнования по созданию персональных AI-агентов. Что это такое? BitGN PAC — это соревнование, где участники создают свои собственные AI-агенты, которые будут решать различные задачи в симулированной среде. Вам предстоит написать ядро агента, подключить его к платформе BitGN через API и …

❤9🔥6😁4

21 Feb 2026, 13:27 UTC≈8,200 views59 reactionsread 29 August 2026
Photo

Во-первых поздравляем всех с праздником масленицы! Во-вторых мы выпустили блогпост про геометрию многообразий внутри LLM: внутри красивые картинки, интересные фичи и интерактивные графики. Рекомендуем темп примерно один блин на главу, приятного аппетита!

❤‍🔥32👍16🔥11

Showing the 12 most recent of 17 posts we hold for @zheltyi_ai. 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.

Forward network

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.

Appears in Telegram’s recommendations for other channels

The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.

Код Желтый
@kod_zheltyi · 33,061
Telegram ranks this channel #7 of 96 here — alongside 95 others — read 4 September 2026
T-Crew
@t_crew · 43,385
Telegram ranks this channel #11 of 95 here — alongside 94 others — read 29 August 2026
Т-Образование
@tbank_education · 113,248
Telegram ranks this channel #17 of 91 here — alongside 90 others — read 14 August 2026
Machinelearning
@ai_machinelearning_big_data · 280,660
Telegram ranks this channel #21 of 95 here — alongside 94 others — read 10 August 2026
gonzo-обзоры ML статей
@gonzo_ML · 24,323
Telegram ranks this channel #22 of 93 here — alongside 92 others — read 16 September 2026
LLM под капотом
@llm_under_hood · 29,146
Telegram ranks this channel #23 of 96 here — alongside 95 others — read 9 September 2026
эйай ньюз
@ai_newz · 96,889
Telegram ranks this channel #26 of 94 here — alongside 93 others — read 16 August 2026
Яндекс Образование
@Education_Yandex · 37,959
Telegram ranks this channel #27 of 96 here — alongside 95 others — read 31 August 2026
ИТ-Пикник
@IT_picnic · 23,242
Telegram ranks this channel #31 of 94 here — alongside 93 others — read 18 September 2026
Yandex for Developers
@Yandex4Developers · 28,505
Telegram ranks this channel #31 of 94 here — alongside 93 others — read 9 September 2026
Время Валеры
@cryptovalerii · 30,829
Telegram ranks this channel #31 of 94 here — alongside 93 others — read 6 September 2026
Data Secrets
@data_secrets · 93,800
Telegram ranks this channel #32 of 98 here — alongside 97 others — read 17 August 2026
Сиолошная
@seeallochnaya · 79,594
Telegram ranks this channel #34 of 97 here — alongside 96 others — read 19 August 2026
Machine learning Interview
@machinelearning_interview · 30,308
Telegram ranks this channel #37 of 98 here — alongside 97 others — read 7 September 2026
Поступашки - ШАД, Стажировки и Магистратура
@postypashki_old · 45,274
Telegram ranks this channel #39 of 90 here — alongside 89 others — read 28 August 2026
Искусственный интеллект. Высокие технологии
@vistehno · 71,491
Telegram ranks this channel #54 of 94 here — alongside 93 others — read 20 August 2026
Ozon Tech
@ozon_tech · 29,730
Telegram ranks this channel #57 of 98 here — alongside 97 others — read 8 September 2026
Data Science
@datascienceiot · 42,642
Telegram ranks this channel #59 of 76 here — alongside 75 others — read 29 August 2026
Data Science Jobs
@datasciencejobs · 22,057
Telegram ranks this channel #62 of 93 here — alongside 92 others — read 21 September 2026
Dev & ML Connectable Jobs
@dev_connectablejobs · 27,750
Telegram ranks this channel #64 of 94 here — alongside 93 others — read 10 September 2026
Sber AI
@SberAIScience · 27,279
Telegram ranks this channel #65 of 95 here — alongside 94 others — read 10 September 2026
Data Science Jobs
@datascienceml_jobs · 21,227
Telegram ranks this channel #74 of 97 here — alongside 96 others — read 24 September 2026
Яндекс нанимает | Вакансии для разработчиков
@ya_jobs · 32,803
Telegram ranks this channel #78 of 96 here — alongside 95 others — read 5 September 2026
Анализ данных (Data analysis)
@data_analysis_ml · 50,631
Telegram ranks this channel #80 of 93 here — alongside 92 others — read 25 August 2026

This channel appears in 26 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. Each is Telegram’s list for THAT channel, not this one — see how this is measured.

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 16 September 2026 — this entry's latest reading, not the date you are reading this.

“Жёлтый AI” (@zheltyi_ai), 9,387 subscribers as measured 16 September 2026. Telegram Register, tgregister.com/channel/zheltyi_ai.

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.