Telegram RegisterThe public register of Telegram

Channel

Data Blog

@jdata_blog

On this record: Growth · Engagement · Reactions · Stars · Posts · Citations · Cite this entry

2,216subscribers

+38 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 1,000–3,162.

Register entry

Telegram ID-1001708314532
TypeChannel
Username@jdata_blog
CreatedBetween 1 December 2021 and 31 March 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live12 August 2026
Measurements held5
Confirmed unchanged1 time, most recently 12 August 2026
On Telegramt.me/jdata_blog

Growth

2,1782,2162,1976 August 2026 — 2,178 subscribers6 August 2026 — 2,178 subscribers6 August 2026 — 2,179 subscribers9 August 2026 — 2,200 subscribers12 August 2026 — 2,216 subscribers6 August 202612 August 2026
5 measurements spanning 7 days, net +38. 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 2,172–2,222 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
12 Aug 2026, 20:442,216+16
9 Aug 2026, 16:222,200+21
6 Aug 2026, 09:102,179+1
6 Aug 2026, 06:062,178no change
6 Aug 2026, 03:072,178first reading

Engagement

17 posts held, back to 19 July 2026the 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.

ERR · 30 days
50.3%
avg views ÷ 2,216 subscribers
Avg views / post
1,110
17 posts measured
Reaction rate
3.02%
reactions ÷ views · ER floor
Posts in window
17
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 4 August 2026
Posts held17 (19 July 20264 August 2026)
Views total18,944
Reactions total572
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Aug 2026, 16:53 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.

Reaction mix

572 reactions across 17 posts, in 13 distinct kinds. The most used accounts for 49.1% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
28149.1%
🔥13223.1%
❤‍🔥335.77%
👍315.42%
🎉305.24%
😱274.72%
😁172.97%
👏101.75%
🦄40.699%
💅20.35%
🤯20.35%
🥰20.35%
🤩10.175%

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 572reactions 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 19 July 2026 to 4 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.

Telegram Stars

Stars received
2
across the posts below
Posts paid on
2
of 17 we hold a reading for · 12%
Most on one post
1
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @jdata_blog. 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 17 most recent posts we hold for this entry, published 19 July 2026 to 4 August 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

4 Aug 2026, 14:03 UTC529 views14 reactionsread 7 August 2026

Чем ещё хотела поделиться — вот прошли выходные (с фикшенными багами), как мы выпустили open-xai. И я смотрю на эти первые 60 пользователей (спасибо вам!), смотрю на наш начальный дизайн, на модули, на обновления в работе — и так хочется улучшать это всё! Мой восторг сменился постепенно на рациональность — мало выпустить продукт, надо думать о UI, UX, доходимости, понятности и кому он нужен, прайс-не прайс, retenti

14

4 Aug 2026, 13:48 UTC459 views8 reactionsread 7 August 2026

Зонды в проде и что послушать/почитать Что такое зонд: Зонд — мини-ML-вида-модель, которая работает на активациях большой модели. Задача такова: Наш Х — скрытое состояние LLM на каждом токене — список матриц (для каждого примера — матрица d × n, где n — длина последовательности, d — внутренняя размерность модели). Не тензор, потому что есть нюансы — скину в комменты. Наш Y на списке матриц — бинкласс — как там сейча

🔥62

4 Aug 2026, 13:48 UTC528 views3 reactionsread 7 August 2026

Что получили, не работает: На джейлбрейках уязвимость минимум на 1% запросов — у всех методов без исключения. Под адаптивным ред-тимингом FNR выбранного авторами зонда — 42%. Так что против обычного трафика зонд — хорошо, а против думающего противника — нет. Общий нюанс: зонду нужен доступ к внутренностям. То есть это инструмент владельца модели или того, кто крутит открытые веса. Сидя на API, зондов нет, но какова

3

31 Jul 2026, 16:02 UTC≈1,350 views73 reactionsread 7 August 2026

Мы выпускаем образовательный ресурс open-xai. Привет, друзья! Я шла к этому очень долго и наконец-то готова выпустить образовательный ресурс open-xai! Ресурс построен как точка, где можно учиться просто всему, что есть в интерпретируемости. От классических методов, до геометрии и математики в моделях. Сейчас в нем: ⁃ 2 трека. XAI Practitioner — объяснять поведение моделей руками, от классики до LLM. Math of LLMs

46🔥19👏4❤‍🔥1🎉1💅1🤯1

30 Jul 2026, 15:38 UTC871 views15 reactionsread 7 August 2026

XAI для агентов: библиотеки Консерватор с тревожкой, когда кто-то что-то делает за него (я), наконец докопался до XAI для агентов. Что у нас есть: С агентами, вместо модели, нас интересует действие и их последовательность. Отсюда мы ставим вопрос: «почему был выбран этот путь/тула/шаг?». На текущем этапе развития интерпретируемости мы бы умерли, если бы тащили для ответа Mech-Interp, потому что у нас появляется га

13💅1🔥1

30 Jul 2026, 15:38 UTC≈1,020 views16 reactionsread 7 August 2026

В целом, мир observability/трейсинга бОльший — Langfuse, Phoenix/Arize, AgentOps, плюс eval-фреймворки типа Inspect. Они все показывают, ЧТО делал агент (логи, шаги, стоимость), но не объясняют ПОЧЕМУ. Это ближе к мониторингу, а не интерпретируемости и тут очень сложно разводить границы. Прикольная карта направления — обзор «Agentic-Transparency» (survey + таксономия). Но сейчас interp (более менее не эксперименталь

12🔥4

28 Jul 2026, 21:12 UTC880 views30 reactionsread 7 August 2026
Photo

Пишу rebuttal эксперименты на NIPS. Статью делали ещё осенью, кажется, так что пришлось заново читать, чтобы осознаться. Так вот — открыла текст не тем редактором — а там prompt injection 🙂 Оказалось: защита NIPSa от LLM-ревью. Вот вам и "сложные времена рождают сложные решения". Счастливых всем rebuttals и пусть удача всегда будет с вами.

😱27😁3

27 Jul 2026, 14:34 UTC997 views17 reactionsread 7 August 2026
Photo

Если лень читать — заходите за красивыми картинками.

14🔥3

27 Jul 2026, 14:33 UTC≈1,000 views27 reactionsread 7 August 2026

Привет, друзья! Как запаковать мир? Всё свободное время я ботаю математику, и это рождает побочную красоту. И наконец-то я добила новый туториал — про то, как модели упаковывают концепты в многообразия. Я била его долго — и он побил меня. Надеюсь, вам понравится! Многообразие — это пространство, которое вблизи каждой точки выглядит как обычная прямая или плоскость, даже если целиком оно замкнуто и искривлено. Мурав

🔥243

24 Jul 2026, 18:29 UTC≈1,120 views27 reactionsread 7 August 2026

Порадовались (друзья, спасибо вам всем громадное!)— структурируемся — вновь свеженькая библиотека — CircuitKIT. Идея библиотеки красивая — упростить процесс работы с цепочками (или схемами, выберите тот перевод на русский, который вам ближе) — circuits. Напоминание: Circuit — минимальный подграф модели (головы + MLP), причинно отвечающий за конкретное поведение. Пример, задача IOI (indirect object identification).

🔥157👍3❤‍🔥2

24 Jul 2026, 18:29 UTC≈1,120 views69 reactions1 Starread 7 August 2026

P.S. Вы — лучшие — я вчера прям на какой-то момент остановилась (вчено куда-то бегу) и поняла, что очень ценю людей вокруг, которые помогают мне двигаться вперед и дальше. Спасибо за все приятнейшие слова и сердечко-огонечки! ❤️‍🔥

50❤‍🔥11👍8

23 Jul 2026, 16:41 UTC≈1,200 views113 reactionsread 7 August 2026
Video message

Video message, posted without a caption

56🎉28❤‍🔥19👏6🦄4

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

Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.

Citation-graph rank

Citation-graph rank — 3,713 of 1,169,250entries 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.

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 8 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.

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

“Data Blog” (@jdata_blog), 2,216 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/jdata_blog.

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.