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 10 September 2026 and assigned it the closest of 31 fixed categories, at 87% 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 the other topics.
Growth
64 measurements spanning 97 days, net -311. 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 13,705–18,015 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 64
Measured (UTC)
Subscribers
Change
11 Nov 2026, 11:36
14,202
-6
9 Nov 2026, 15:21
14,208
-2
8 Nov 2026, 10:17
14,210
-4
7 Nov 2026, 03:21
14,214
+9
6 Nov 2026, 02:59
14,205
-5
5 Nov 2026, 00:45
14,210
-2
3 Nov 2026, 22:30
14,212
+4
2 Nov 2026, 22:25
14,208
-4
2 Nov 2026, 00:34
14,212
-9
1 Nov 2026, 02:37
14,221
-3
31 Oct 2026, 04:27
14,224
+5
30 Oct 2026, 03:20
14,219
-10
29 Oct 2026, 05:39
14,229
+2
28 Oct 2026, 01:57
14,227
+11
26 Oct 2026, 23:16
14,216
-1
26 Oct 2026, 00:50
14,217
+1
25 Oct 2026, 04:07
14,216
-2
24 Oct 2026, 02:18
14,218
-2
23 Oct 2026, 00:49
14,220
-6
22 Oct 2026, 03:18
14,226
first reading
Engagement
71 posts held, back to 8 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 68 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
19.8%
avg views ÷ 14,202 subscribers
Avg views / post
2,810
26 posts measured
Reaction rate
0.851%
reactions ÷ views · ER floor
Posts in window
26
of 71 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 8 November 2026
Posts held
71 (8 July 2026 – 8 November 2026)
Views total
73,000
Reactions total
621
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
11 Nov 2026, 07:24 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
1m 31s
Average length
23s
Measured directly from 4 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.
Reaction mix
1,720 reactions across 70 posts, in 16 distinct kinds. The most used accounts for 34.1% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
😁
586
34.1%
❤
534
31.0%
👍
256
14.9%
🔥
166
9.65%
🏆
53
3.08%
💯
42
2.44%
🎉
20
1.16%
🎃
15
0.872%
custom 5787518600872988853
10
0.581%
⚡
9
0.523%
🤯
9
0.523%
custom 5442983582882601962
8
0.465%
custom 5224708023435404637
6
0.349%
custom 5377424136924577004
4
0.233%
custom 5787319048102482011
1
0.058%
😈
1
0.058%
Custom emoji. 5 of the rows above are Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The counts beside them are Telegram’s.
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 70 of the 71 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 1,720 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 71 most recent posts we hold, published 8 July 2026 to 8 November 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
30
across the posts below
Posts paid on
5
of 71 we hold a reading for · 7%
Most on one post
22
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @datafeeling. 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 71 most recent posts we hold for this entry, published 8 July 2026 to 8 November 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.
Recent posts
Telegram’s own ‘edited’ marker: 14 of 26 posts held from the last 30 days (53.8%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
В сети распространяется странный эксперимент.
Загрузите фото комнаты и попросите ИИ: «Заполни её тем, что ты знаешь обо мне».
Мой результат меня удивил. Я и так понимал, что приложения собирают о нас информацию. Но одно дело — знать это, и совсем другое — увидеть всё в виде картинки.
Кидайте свои варианты в комменты. Мой в первом комментарии
Алгоритм знает, где вы будете 7-го ноября 😎
RecSys-митап в Москве для тех, кто уже строит рекомендательные системы и хочет делать это еще лучше.
В программе — доклады от топовых экспертов Сбера с разбором кейсов, свежих подходов и неочевидных решений.
После официальной части — нетворкинг. Время в узком кругу профессионалов и сообщества Зеленый RecSys.
Участие бесплатное, но количество мест ограничено.
Москва. Су…
Мир разделился на две группы. И граница прошла по Claude Code
На этой неделе Anthropic снова прошлась катком по аккаунтам, которые связаны с Россией. У знакомых слетели подписки, рабочие чаты и проекты, которые жили в Claude месяцами.
Мой пример. У меня на компе почти всё делает Claude Code. Через MCP он ходит в мои сервисы, через computer use сам кликает по интерфейсам, сам собирает интеграции, пишет код, деплоит,…
Вот вам даже пруф с поздравлением потом другого друга через этот сервис. Как вам качество?
Если вам в голову пришла идея сервиса поздравления персональными песнями, мультиками, стихами, сказками и тп, то забейте.
Тут нулевая устойчивость к копированию. Их уже или скоро будет больше чем самих потенциальных именинников.
Стоит браться только, если вы реально сможете выделиться на фоне других 1000+ сервисов, которыми …
Сделал сервис за один вечер и подарил на день рождения
Есть такой движ - build in public. Рассказываешь про свой продукт задолго до релиза и собираешь вокруг него первую аудиторию.
С приходом вайбкодинга эта схема посыпалась. Билдеров и продуктов стало столько, что внимания на всех уже не хватает.
А добили её клоны. Свежий анонс через пару дней копируют под ноль. Самый громкий пример - игру "Hay in the stack" (иго…
Если вы думали что вы такой один, то нет
Примерно 1 000 000 акаунтов Claude, связанных с РФ было заблокировано.
Жесть конечно. Я успел провести ресерч для вас. Из сильных альтернатив хорошо работает GLM 5.3. Вполне себе на равных с Opus 5.5. Как альтернатива норм.
Пользуйтесь.
36 стартапов только что подняли по $5-10M. Что из этого забрать себе
На днях завирусилась подборка: «36 стартапов, которые за последние недели подняли по $5-10M, в каждом 10-50 человек, и все нанимают».
Я разложил список по кучкам, и картина вышла интересная.
Треть - железо и наука: ИИ-вычисления на спутниках, лазерный термояд размером с тумбочку, генное редактирование, двухместный электросамолёт. Это игра фондов …
6 фаундеров, которые нашли идею у себя под носом
Прошлые два поста были про рынки и места, где искать идеи. Сегодня - как это делали фаундеры, которые уже заработали. У всех один паттерн: идея лежала в том, чем они и так занимались.
1. Свой офлайн-бизнес. GetRoute сначала разогнали клининговую компанию до $10M выручки, а потом запустили софт для таких же клининговых бизнесов. Свою боль они знали наизусть.
2. Свои …
👍11🎉1
Signed Aleron Milenkin
Showing the 12 most recent of 71 posts we hold for @datafeeling. 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.
Posts edited after publishing
@datafeeling edited 4 posts after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
First edit seen
9 August 2026
Most recent edit
19 August 2026
Forward network
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.
Mentions
Named by 15 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.
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.
Время Валеры @cryptovalerii · 32,082 Telegram ranks this channel #8 of 94 here — alongside 93 others — read 6 September 2026
Stepik – онлайн-курсы @stepik_courses · 28,865 Telegram ranks this channel #9 of 93 here — alongside 92 others — read 16 September 2026
Machine learning Interview @machinelearning_interview · 30,560 Telegram ranks this channel #10 of 98 here — alongside 97 others — read 7 September 2026
Data Science Jobs @datasciencejobs · 22,587 Telegram ranks this channel #13 of 93 here — alongside 92 others — read 21 September 2026
XOR @xor_journal · 195,549 Telegram ranks this channel #14 of 93 here — alongside 92 others — read 12 August 2026
karpov.courses @KarpovCourses · 27,313 Telegram ranks this channel #15 of 96 here — alongside 95 others — read 10 September 2026
Dev & ML Connectable Jobs @dev_connectablejobs · 29,105 Telegram ranks this channel #15 of 94 here — alongside 93 others — read 10 September 2026
Data Secrets @data_secrets · 96,035 Telegram ranks this channel #15 of 98 here — alongside 97 others — read 17 August 2026
Yandex for ML @yandexforml · 19,136 Telegram ranks this channel #16 of 96 here — alongside 95 others — read 4 October 2026
Data Science Jobs @datascienceml_jobs · 21,642 Telegram ranks this channel #18 of 97 here — alongside 96 others — read 24 September 2026
Анализ данных (Data analysis) @data_analysis_ml · 51,923 Telegram ranks this channel #19 of 93 here — alongside 92 others — read 25 August 2026
Data Science | Machinelearning [ru] @devsp · 19,659 Telegram ranks this channel #22 of 91 here — alongside 90 others — read 30 September 2026
LLM под капотом @llm_under_hood · 30,219 Telegram ranks this channel #25 of 96 here — alongside 95 others — read 9 September 2026
Kali Novskaya @rybolos_channel · 19,136 Telegram ranks this channel #26 of 93 here — alongside 92 others — read 4 October 2026
Machinelearning @ai_machinelearning_big_data · 275,659 Telegram ranks this channel #27 of 95 here — alongside 94 others — read 10 August 2026
Поступашки - ШАД, Стажировки и Магистратура @postypashki_old · 47,200 Telegram ranks this channel #33 of 90 here — alongside 89 others — read 28 August 2026
Инжиниринг Данных @rockyourdata · 23,679 Telegram ranks this channel #34 of 93 here — alongside 92 others — read 17 September 2026
Поколение Python 🐍 @pygen_ru · 50,348 Telegram ranks this channel #36 of 93 here — alongside 92 others — read 25 August 2026
эйай ньюз @ai_newz · 98,339 Telegram ranks this channel #37 of 94 here — alongside 93 others — read 16 August 2026
Sber AI @SberAIScience · 26,483 Telegram ranks this channel #42 of 95 here — alongside 94 others — read 10 September 2026
Noukash @noukashblog · 21,573 Telegram ranks this channel #44 of 95 here — alongside 94 others — read 23 September 2026
Артём Шумейко @artemshumeiko · 19,769 Telegram ranks this channel #45 of 92 here — alongside 91 others — read 29 September 2026
LEFT JOIN @leftjoin · 41,485 Telegram ranks this channel #45 of 95 here — alongside 94 others — read 29 August 2026
Job for Analysts & Data Scientists @foranalysts · 37,857 Telegram ranks this channel #46 of 96 here — alongside 95 others — read 1 September 2026
This channel appears in 33 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 11 November 2026 — this
entry's latest reading, not the date you are reading this.
“🏆 AIeron | Data Feeling” (@datafeeling), 14,202 subscribers as measured 11 November 2026. Telegram Register, tgregister.com/channel/datafeeling.
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.