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Channel

epsilon correct

@epsiloncorrect

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

8,095subscribers

+2 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-1001460410767
TypeChannel
Username@epsiloncorrect
DescriptionМашинное обучение, графы, языковые модели. Чуток про карьеру исследователя в FAANG, путь PhD и щепотка полезной математики. Связаться с автором: @deltaincorrect. Рекламы в канале нет.
Created18 September 2022measured — cross-checked against a third-party dataset (ext.tg_channel)
First recorded6 August 2026
Last confirmed live12 August 2026
Measurements held5
Confirmed unchanged1 time, most recently 12 August 2026
On Telegramt.me/epsiloncorrect

Growth

8,0938,0958,0946 August 2026 — 8,093 subscribers6 August 2026 — 8,093 subscribers6 August 2026 — 8,095 subscribers9 August 2026 — 8,094 subscribers12 August 2026 — 8,095 subscribers6 August 202612 August 2026
5 measurements spanning 5 days, net +2. 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 8,093–8,095 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
12 Aug 2026, 01:128,095+1
9 Aug 2026, 11:328,094-1
6 Aug 2026, 21:408,095+2
6 Aug 2026, 19:008,093no change
6 Aug 2026, 18:498,093first reading

Engagement

20 posts held, back to 15 December 2025the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 11 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
48.2%
avg views ÷ 8,095 subscribers
Avg views / post
3,910
2 posts measured
Reaction rate
1.27%
reactions ÷ views · ER floor
Posts in window
2
of 20 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 18 July 2026
Posts held20 (15 December 202518 July 2026)
Views total7,810
Reactions total99
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken12 Aug 2026, 16:47 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
182
Videos
7
Links
241

Lifetime counters from Telegram’s own channel header, read 12 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.

Reaction mix

1,301 reactions across 20 posts, in 18 distinct kinds. The most used accounts for 40.8% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥53140.8%
30723.6%
👍1118.53%
🤣967.38%
👏614.69%
🌚443.38%
🎉272.08%
👀211.61%
🤪211.61%
😭201.54%
🤝161.23%
🤔130.999%
🙏110.846%
🥴90.692%
😱60.461%
👎40.307%
💅20.154%
🍓10.077%

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 20 of the 20 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 1,301reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 20 most recent posts we hold, published 15 December 2025 to 18 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.

Telegram Stars

Stars received
42
across the posts below
Posts paid on
6
of 20 we hold a reading for · 30%
Most on one post
25
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @epsiloncorrect. 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 20 most recent posts we hold for this entry, published 15 December 2025 to 18 July 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

18 Jul 2026, 11:26 UTC≈3,370 views44 reactionsread 12 August 2026

Куртку продали за $960.000 Если купили дорогие подпищеки, дайте поносить?

🤣41🤪2🔥1

16 Jul 2026, 02:52 UTC≈4,440 views55 reactionsread 12 August 2026
Photo

у нашей с вами любиой геммы пофиксили темплейт чата, стало лучше на бенчах 👀 бежим качать обновление с хф

🔥40🤪15

7 Jul 2026, 10:26 UTC≈6,090 views24 reactionsread 12 August 2026

Техрепорт Gemma 4 наконец-то докатился до архива ☺️, особо ничего нового, немного больше эвалов в long-context и для аудио

🔥12👀10🙏2

3 Jul 2026, 08:02 UTC≈7,430 views58 reactionsread 12 August 2026
Photo

Мечта всех, кто хотел кожаночку как у Дженсена Хуанга – на следующем Sotheby's можно будет купить подписанную им куртку Tom Ford. Средства пойдут на благотворительность, ориентировочная цена – 40-60k$, хотя зачастую у аукционных домов не всё хорошо с оценкой спроса, и куртка может уйти за сильно больше какому-нибудь сотруднику фронтирной лабы. Если кто-то из дорогих подпищеков купит – маякните 😎

🤣44😱6👎4🥴31

2 Jul 2026, 13:26 UTC≈6,970 views50 reactionsread 12 August 2026
Photo

Пока я откисаю в Корее от очередного сезона исхода дорогих коллег [1, 2, 3, и др.] перед ICML, наша с читателями любимая Лилиан Вэн – авторка топ-1 блога по диплёрнингу – написала первый за почти два года пост про историю и развитие науки об оценке правил масштабирования (scaling laws) языковых моделей. Почему "правил", а не "законов" – чтобы не создавать ощущения универсальности самих законов: всех необходимых факто

38🔥7😭3👏1🤝1

18 Jun 2026, 23:19 UTC≈6,530 views56 reactions1 Starread 12 August 2026
Photo

Проверяемся, запомнили ли вас ллмки на intheweights.com Гпт 5.5 меня задизреспектила 😭

39😭17

5 May 2026, 16:52 UTC≈8,520 views59 reactionsread 12 August 2026
Photo

MTP спекулятивный декодинг в Gemma 4: ускоряемся в два раза без потери качества 🥳 В нашу дорогую гемму наконец завезли спекулятивный декодинг, когда более маленькая модель предсказывает токены, которые могут верифицироваться большой моделью параллельно, существенно ускоряя инференс для локальных юзкейзов. Попробовать можно через HuggingFace transformers, остальные движки тоже скоро будут поддерживать. Поглубже почи

🔥4811

16 Apr 2026, 14:35 UTC≈14,000 views102 reactionsread 12 August 2026
Photo

Продолжаем геммапропаганду. В прошлом году у NVIDIA вышла неплохая статья о том, как ловить людей, которые доливают тест в трейн. CoDeC – нормализованный показатель перплексии, где для тестсета бенчмарка считают изменения в перплексии с дополнительными примерами из того же бенчмарка. Для неконтаминированных моделек мы ожидаем, что дополнительные примеры не будут сбивать модель с толку, а в лучшем случае помогут. С др

🔥75🤔13🤣10🤪4

10 Apr 2026, 13:50 UTC≈10,200 views55 reactionsread 12 August 2026
Photo

WeirdML – один из самых необычных бенчмарков для ЛЛМок. В него входят необычные open-ended задачки по МЛю, например, написание МЛ пайплайнов по распознаванию цифр со всего 28 размеченными примерами и ~50к неразмеченными, предсказание формы фигур, или восстановление перемешанных фрагментов изображений. Gemma 4 31B оказалась самой сильной открытой моделью на этом бенчмарке, опередив GLM 5 (MoE на 700B) и GPT-OSS с хор

🔥37👍153

4 Apr 2026, 01:42 UTC≈10,200 views38 reactionsread 12 August 2026
Photo

Мои любимые artificial analysis выложили своё независимое тестирование Gemma 4 (твит, страница с результатами), по результатам вышло хуже квенов из-за просадки на 𝜏²-bench, ну и ладно с ним. На картинку с бенчмарками можно позалипать в комментариях к посту. В этой версии мне довелось поработать над околонаучными бенчмарками и работой с длинным контекстом, а там мы наступаем на пятки китайским моделям на порядок боль

👍25👀11🔥2

2 Apr 2026, 16:02 UTC≈14,200 views103 reactions1 Starread 12 August 2026
Photo

Gemma 4 blogpost | model card | huggingface 4 размера: E2B, E4b (бывшие Gemma 3n/Gemini Nano); 26A4B, 31B Dense. Теперь лицензия Apache 2.0! Для всех моделей релизим претрейн и intruction tuned чекпойнты. Context length 256k у 31B модельки, 128k у остальных. Скажу по секрету – можно пробовать и больше, должно работать. LLM Arena на уровне Kimi 2.5, бенчмарки можно посмотреть на huggingface

53🔥44🎉5🤣1

10 Mar 2026, 17:58 UTC≈7,360 views84 reactions25 Starsread 12 August 2026
Photo

Gemini embedding 002 блог | API docs Первые по-настоящему мультимодальный эмбеддинги от нас. Теперь можно за в один эмбеддинг загнать до 8к токенов текста, 6 картинок, 120 секунд видео, 80 секунд аудио или 6 страниц PDF. Цены почти не изменилась – с $0.15/MTok до $.20/MTok, для batch использования – вдвое дешевле. В этой версии сильно улучшили качество эмбеддингов по коду, теперь распознаёт больше языков. Улучшили

🔥6513👏6

Showing the 12 most recent of 20 posts we hold for @epsiloncorrect. 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 — 331,700 of 1,160,990entries 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.

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.

Machinelearning
@ai_machinelearning_big_data · 286,250
Telegram ranks this channel #57 of 95 here — alongside 94 others — read 10 August 2026

This channel appears in 1 seed channel's Telegram-generated recommendation list in total. 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 12 August 2026 — this entry's latest reading, not the date you are reading this.

“epsilon correct” (@epsiloncorrect), 8,095 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/epsiloncorrect.

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.