Telegram RegisterThe public register of Telegram

Channel

зAIцы в экономе

@databeadgame

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

33subscribers

+0 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1001562532862
TypeChannel
Username@databeadgame
DescriptionМашинное обучение с экономическим привкусом
CreatedBetween 1 August 2021 and 31 January 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded11 August 2026
Last confirmed live11 August 2026
Measurements held2
On Telegramt.me/databeadgame

Growth

337 August 2026 — 33 subscribers11 August 2026 — 33 subscribers7 August 202611 August 2026
2 measurements spanning 3 days. 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 32–34 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
11 Aug 2026, 01:3233no change
7 Aug 2026, 18:5533first reading

Engagement

17 posts held, back to 14 April 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
54.5%
avg views ÷ 33 subscribers
Avg views / post
18.0
2 posts measured
Reaction rate
this channel exposes no reaction counts
Posts in window
2
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 22 July 2026
Posts held17 (14 April 202622 July 2026)
Views total36
Reactions total
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken11 Aug 2026, 01:32 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

Photos
25
Videos
2
Links
35

Lifetime counters from Telegram’s own channel header, read 11 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.

Video runtime
1m 03s
Average length
1m 03s

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

17 reactions across 8 posts, in 6 distinct kinds. The most used accounts for 29.4% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍529.4%
🔥423.5%
🥰317.6%
211.8%
👏211.8%
💯15.88%

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 8 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 17reactions 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 14 April 2026 to 22 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.

Recent posts

9 Jul 2026, 10:12 UTC35 viewsread 11 August 2026

#эконом Дописал пост про permanent underclass - феномен, широко обсуждаемый в англоязычном сегменте Если тревожитесь, что ИИ запрет вас в бедности, то велкам под кат https://vas3k.club/post/32041

2 Jul 2026, 12:07 UTC39 viewsread 11 August 2026
Photo

Так как реакций на текст не вижу, держите мемес к обзору выше

30 Jun 2026, 09:42 UTC34 views2 reactionsread 11 August 2026

#эконом Наконец-то нашел крутую хайповую статью по теме канала про то, почему компании могут рационально идти к коллективно плохому результату, автоматизируя работу с помощью ИИ - "The AI Layoff Trap" (https://arxiv.org/pdf/2603.20617) Модель простая. Каждая компания, заменяя сотрудников ИИ, получает весь эффект: экономит на зарплатах. Но негативный эффект — сокращение доходов работников и, следовательно, спроса —

👏2

29 Jun 2026, 12:11 UTC23 viewsread 11 August 2026
Photo

#ллм Написал пост для линкдина, но главное там конечно мемес, а не цитата антропиков Держите рус версию (в линке можно полайкать англ ) Почему я настороженно отношусь к LangChain/LangGraph в проде (а у моей компании прям горит, чтоб запихнуть их куда-нибудь): 1. Оверхед для простых задач Многие LLM-флоу — это просто запрос → retrieval/tool call → LLM → проверка ответа. Не всегда нужны графы, планировщики и нескол

4 Jun 2026, 08:17 UTC30 views2 reactionsread 11 August 2026

#ллм Но и джуны в универе должны учиться думать, а не решать домашки через чатгпт ИИ в айти образовании не делает его легче, скорее наоборот, теперь психологически надо заставлять себя копать глубже, чем чатгпт предлагает + объем постоянно растет. Вангую рост спроса на экспертов образовательной траектории, которые не только в рамках всей программы будут рекомендовать, что набирать, но и внутри одной сферы выстраив

2

4 Jun 2026, 08:11 UTC28 views1 reactionsread 11 August 2026
Forwarded from @neuraldeep

Человек-оркестр это не мем это диагноз Люблю этот летний утренний хайп сегодня "накидал агентов они сами всё сделали ты только оркестрируешь, кодинг умер инженеры не нужны!!!" Так вот скажу как человек который завёл первый MVP хаба за вечер на клоде (11 контейнеров, 15к строк), а потом полтора месяца и 693 коммита доводил его до того что он реально держит прод и принимает деньги Демка взлетает за сутки, а продукт

🔥1

4 Jun 2026, 08:11 UTC19 views1 reactionsread 11 August 2026

#ллм Реальный опыт реального инженера Поэтому я против сокращения найма джунов, даже если сейчас это кажется чистыми затратами, на долгосроке упремся в жёсткую нехватку кадров, которые умеют работать головой и обладают фундаментом

💯1

18 May 2026, 19:12 UTC34 viewsread 11 August 2026
Photo

#ллм Ютуб порекомендовал видео, которое очень похоже на другой мой недоделанный пет проект https://youtu.be/FlzpEGHNVKQ?is=jtGb3b45k-3-E7WR Я пытался делать коуча для шахмат, который бы не просто говорил линию по стокфишу, но и объяснял наиболее вероятный человеческий ход и какие ловушки есть походу. Магнус Карлсон подумал также, поэтому ребята из его стартапа сделали похожего коуча. На входе эвристики для такти

15 May 2026, 19:49 UTC31 views3 reactionsread 11 August 2026
Video

#разное У меня заканчивается очередной семестр изучения китайского, и как-то чувствуется, что можно учиться поэффективнее. В целом, в Бельгии преподам как-то немного пофиг на то, выучил ты что-то или нет. Поэтому сделал мвп аппки, которая помогает идти по стандартному учебнику HSK - грузишь фото урока, он распознает новую лексику, делает карточки с ними, выделяет грамматику, сочиняет предложение на перевод с ней.

🔥3

24 Apr 2026, 14:13 UTC44 views4 reactionsread 11 August 2026

#ллм Заодно сравнил новый Клод дизайн и Гугл стич Оба инструмента на замену фигме и возможно UI/UX дезигнерам Прогнал тест на генерацию интерфейса для внутреннего сервиса. Буквально два параграфа требований. Стич неплохо оформил дополненные требования в документ, но сама генерация заняла время, и сам веб-сайт достаточно медленный для частых итераций. Результат работал, но выглядело стандартно. А вот Клод с перво

👍4

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

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.

Mentions

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.

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

“зAIцы в экономе” (@databeadgame), 33 subscribers as measured 11 August 2026. Telegram Register, tgregister.com/channel/databeadgame.

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.