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Channel

LLM под капотом

@llm_under_hood

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Citations · Handles named that no longer answer · Telegram's recommendations · Cite this entry

30,149subscribers

+1,620 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1001943579488
TypeChannel
Username@llm_under_hood
CreatedBetween 1 April 2023 and 31 October 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live7 November 2026
Measurements held61
Confirmed unchanged1 time, most recently 7 November 2026
On Telegramt.me/llm_under_hood

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 10 September 2026 and assigned it the closest of 31 fixed categories, at 99% 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

28,52930,14929,3396 August 20267 November 2026
61 measurements spanning 93 days, net +1,620. 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 28,286–30,392 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 61
Measured (UTC)SubscribersChange
7 Nov 2026, 14:5130,149+28
6 Nov 2026, 12:4030,121+14
5 Nov 2026, 15:2130,107+25
4 Nov 2026, 12:5530,082+2
3 Nov 2026, 12:0930,080+24
2 Nov 2026, 09:5930,056+13
1 Nov 2026, 09:5930,043+24
31 Oct 2026, 09:1630,019+30
30 Oct 2026, 06:4129,989+35
29 Oct 2026, 06:4129,954+37
28 Oct 2026, 06:2929,917+46
27 Oct 2026, 04:0729,871+23
26 Oct 2026, 05:1029,848+24
25 Oct 2026, 05:2529,824+1
24 Oct 2026, 05:5929,823+28
23 Oct 2026, 03:0629,795+18
22 Oct 2026, 03:5129,777+26
20 Oct 2026, 23:5429,751+13
20 Oct 2026, 01:1629,738+22
19 Oct 2026, 04:1829,716first reading

Engagement

83 posts held, back to 2 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 151 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
33.5%
avg views ÷ 30,149 subscribers
Avg views / post
10,100
28 posts measured
Reaction rate
0.712%
reactions ÷ views · ER floor
Posts in window
28
of 83 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 6 November 2026
Posts held83 (2 July 2026 – 6 November 2026)
Views total282,570
Reactions total2,013
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Nov 2026, 11:36 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
3m 21s
Average length
3m 21s

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

7,153 reactions across 83 posts, in 19 distinct kinds. The most used accounts for 36.5% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥2,61436.5%
❤1,96827.5%
👍1,60522.4%
😁2573.59%
💯1181.65%
👏921.29%
😢871.22%
🤣751.05%
🤯741.03%
🤗710.993%
🤔640.895%
🤝340.475%
🥰250.35%
😱220.308%
🙏160.224%
🤩100.14%
⚡90.126%
👨‍💻80.112%
🎄40.056%

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 83 of the 83 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 7,153 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 83 most recent posts we hold, published 2 July 2026 to 6 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.

Recent posts

Telegram’s own ‘edited’ marker: 20 of 28 posts held from the last 30 days (71.4%) 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).

6 Nov 2026, 11:02 UTC≈4,330 views54 reactionsread 7 November 2026

Posted without readable text

🔥38❤8👍5🤝3

5 Nov 2026, 14:24 UTC≈5,870 views34 reactionsread 7 November 2026
Photo

Наш агент напишет вашему агенту С одной стороны это смешно, а с другой стороны начинает происходить у нас в команде все чаще, по мере того, как привычные human-driven процессы начинают ускоряться агентами. На скриншоте пример процесса передачи рабочего контекста с материалами от одного агента другому. Итак, мы работаем над обучающей платформой. После прогона первой когорты набрались идеи по улучшению продукта. @ak…

👍20❤8🔥4🤣2

4 Nov 2026, 14:35 UTC≈6,840 views61 reactionsread 7 November 2026

Почему Ринат не пишет своих агентов В комментариях к прошлому посту было много отсылок на разные agentic харнесы, которые уже давно реализовали у себя разговорную память. Да что там говорить, нативная работа с ней даже есть у ChatGPT. И это круто. Но я никогда не буду писать свой агентский харнес или пытаться конкурировать с существующими. Но вот что я делаю у нас в BitGN - так это свой слой памяти, в который могут…

❤35👍20🔥5🤯1

4 Nov 2026, 07:45 UTC≈7,400 views111 reactionsread 7 November 2026

Ускоряем работу с памятью Codex - conversation index Codex/Claude Code сохраняют на диск историю разговоров. На эти разговоры можно было раньше ссылаться со словами "посмотри в историю сессий в ~/.codex/sessions и скажи, что можно тут улучшить". Все работает неплохо. Но вчера во время начала внедрения Company Brain в новую компанию, я понял, что все может быть гораздо лучше, а мне прямо срочно нужна отдельная база …

🔥58👍30❤19🤩4

29 Oct 2026, 12:58 UTC≈10,900 views117 reactionsread 7 November 2026
Photo

Насколько просто можно найти потрясающего специалиста в 2026 году Если помните, эксперимент коммьюнити с BitGN Brain с роем в 30 агентов (который решал задачи ECOM1) пришлось поставить на паузу после того, как слой версионирования выел весь доступный диск. Поэтому я сел переписывать storage. Позвал Codex и велел сделать архитекутуру понятной, упростить, но при этом масштабировать под ECOM2. Выдал ему дамп с работо…

🔥78❤22👍5😢5⚡3💯2🤯1😱1

28 Oct 2026, 10:14 UTC≈10,700 views61 reactionsread 7 November 2026
Photo

Ментальная модель организации проектов без скилов Как я уже говорил, я не использую скилы при разработке. Вместо них использую единый и простой progressive disclosure, который не замусоривает контекст, единообразно работает между разными харнесами и неплохо масштабируется на большие проекты/команды. На картинке как раз схема того, как это все укладывается у меня в голове. Причем, эта же схема "Progressive Disclosu…

❤32🔥16🤗7👍4🎄1💯1

27 Oct 2026, 11:12 UTC≈9,300 views54 reactionsread 7 November 2026

Что происходит в канале - часть 4 Вчера я упомянул видео от YCombinator про организацию AI Native Company, что они описывают даже принцип работы роя агентов, который мы запускали в этом коммьюнити. Давайте поговорим про это подробнее. Напомню, что мы продолжаем разбирать фразу: Если кратко - рой агентов нашего коммьюнити пишет агента для автоматизации сложных задачек e-commerce используя только локальные LLM. Они …

❤29🔥21👍2😁2

26 Oct 2026, 13:27 UTC≈8,620 views49 reactionsread 7 November 2026
Photo

А вот пример того, как company brain работает в команде Вот такое сообщение мне сейчас прислал Company Brain. Его попросили из Codex-а заархивировать обновленный прототип проекта для передачи мне и интеграции. Но вместо того, чтобы просто загрузить файл и выдать ссылку для пересылки (бред, да?) - он на этом не остановился, а нашел инструмент message и меня в списке разрешенных адресатов. Это ему позволило сразу взя…

👍26❤16👏3🤔2🥰1😢1

26 Oct 2026, 12:02 UTC≈8,860 views45 reactionsread 7 November 2026

Смотрите, что YCombinator говорит про принцип работы роя агентов, такого же, который мы уже запускали вместе в рамках моделирования работы небольшой организации - AI R&D лабы! Building And Structuring An AI Native Company (YouTube) Наша технология пока на шаг впереди их видения company brain (есть работающее взаимодействие агентов, которые позволяют включить режим работы роя), но это видео все равно очень вдохновля…

🔥31🥰5❤4👏3⚡1👍1

24 Oct 2026, 15:12 UTC≈8,840 views81 reactionsread 7 November 2026

Что происходит в канале - часть 3? Память роя закончилась, рой засыпает до следующей недели. А мы продолжаем разбирать фразу (оглавление): Если кратко - рой агентов нашего коммьюнити пишет агента для автоматизации сложных задачек e-commerce используя только локальные LLM. Они делают это используя совместную память Company Brain. Рой был запущен прошлым вечером и довел точность до 78.30. Итак, мы поговорили про за…

🔥40❤35👍5🤣1

23 Oct 2026, 07:05 UTC≈9,650 views45 reactionsread 7 November 2026

Рой вышел в TOP-10 ECOM1 Prod (интерлюдия) Результативность - 95.1 (лидерборд) Но при этом в чате говорят, что он немного разленился и начал пихать regex-ы в решения. Формально это тоже решение, но такое себе с точки зрения переиспользования в других проектах. В принципе логично, что мы до такого докатились - у задачи не было жестких критериев качества, только стремление выбить максимальное число баллов. Там даже …

❤33🔥12

22 Oct 2026, 15:16 UTC≈9,250 views56 reactionsread 7 November 2026

Что происходит в канале? Часть 2 Итак, продолжаем разбирать фразу Если кратко - рой агентов нашего коммьюнити пишет агента для автоматизации сложных задачек e-commerce используя только локальные LLM. Они делают это используя совместную память Company Brain. Рой был запущен прошлым вечером и довел точность до 78.30. Оглавление тут. Мы обсудили, что агенты совместно решают задачки по автоматизации commerce. Дальше…

🔥28👍14🤯6❤5💯2🤣1

Showing the 12 most recent of 83 posts we hold for @llm_under_hood. 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

@llm_under_hood edited 1 post 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
24 October 2026
Most recent edit
26 October 2026

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 49 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. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.

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.

Channels Telegram recommends alongside this one

Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.

Сиолошная
@seeallochnaya · 81,058
#1
эйай ньюз
@ai_newz · 98,249
#2
Старший Авгур
@senior_augur · 8,364
#3
Denis Sexy IT 🤖
@denissexy · 140,483
#4
Dealer.AI
@dealerAI · 17,083
#5
Kali Novskaya
@rybolos_channel · 19,139
#6
Время Валеры
@cryptovalerii · 32,031
#7
Градиент обреченный
@doomgrad · 8,845
#8
Борис опять
@boris_again · 17,974
#9
Data Secrets
@data_secrets · 96,013
#10
что-то на DL-ском
@nadlskom · 5,149
#11
Machinelearning
@ai_machinelearning_big_data · 276,026
#12
еба́ные идеи для резерча
@ebaresearch · 5,370
#13
DeepSchool
@deep_school · 10,728
#14
Агенты ИИ | AGI_and_RL
@AGI_and_RL · 6,274
#15
e/acc
@cryptoEssay · 63,672
#16
Пресидский залив
@neural_prosecco · 8,418
#17
Дратути Антон
@blog_toxa · 4,362
#18
Complete AI
@complete_ai · 7,880
#19
РИСЕРЧОШНАЯ
@researchoshnaya · 2,464
#20
КПД
@quant_prune_distill · 3,510
#21
AI[ex]Time
@AIexTime · 2,860
#22
Жёлтый AI
@zheltyi_ai · 9,371
#23
Ppprompt | Sexy AI Prompts & Experiments | by @ponchiknews
@ppprompt · 15,553
#24
🏆 AIeron | Data Feeling
@datafeeling · 14,214
#25
AI Product | Igor Akimov
@ai_product · 8,383
#26
AI для Всех
@nn_for_science · 15,469
#27
AbstractDL
@abstractDL · 18,844
#28
epsilon correct
@epsiloncorrect · 8,198
#29
Нескучный Data Science
@not_boring_ds · 12,081
#30
Mashkka про Data Science
@mashkka_ds · 5,305
#31
Generative Anton
@repushko_channel · 5,447
#32
Нейронный Кот
@neural_cat · 1,532
#33
Yandex for ML
@yandexforml · 19,132
#34
DLStories
@dl_stories · 15,546
#35
DL in NLP
@dlinnlp · 11,508
#36
Запрети мне псевдолейблить
@pseudolabeling · 4,493
#37
Al Talent Hub
@aitalenthubnews · 7,826
#38
Kantor.AI
@kantor_ai · 12,216
#39
partially unsupervised
@partially_unsupervised · 10,559
#40
я обучала одну модель
@def_model_train · 4,468
#41
Rebryk Blog
@rebrykblog · 12,083
#42
EDU
@ProductsAndStartups · 15,350
#43
Machine learning Interview
@machinelearning_interview · 30,569
#44
ML — это ОК
@mlvok · 2,097
#45
AI VK Hub
@aihubvk · 2,483
#46
Pavel Zloi
@evilfreelancer · 4,746
#47
Клиенты для SaaS | Гоша Токмаков
@llmers · 781
#48
vlad kooklev — ai & agents
@prod1337 · 7,461
#49
DL Paper Reviews
@dl_paper_reviews · 473
#50
BOGDANISSSIMO
@bogdanisssimo · 7,014
#51
Техножрица 👩‍💻👩‍🏫👩‍🔧
@tech_priestess · 15,115
#52
New Yorko Times
@new_yorko_times · 10,705
#53
Метаверсище и ИИще
@cgevent · 53,530
#54
addmeto
@addmeto · 72,001
#55
kyrillic
@kyrillic · 61,164
#56
ODS #jobs
@odsjobs · 14,561
#57
grokaem себя
@grokaem_seby · 2,756
#58
Just links
@j_links · 6,946
#59
Data, Stories and Languages
@datastorieslanguages · 3,854
#60
AI Happens
@aihappens · 14,533
#61
Neural Shit
@NeuralShit · 54,647
#62
Сергей Марков: машинное обучение, искусство и шитпостинг
@oulenspiegel_channel · 12,333
#63
Сергей Булаев AI 🤖
@sergiobulaev · 12,608
#64
Dev & ML Connectable Jobs
@dev_connectablejobs · 29,061
#65
Derp Learning
@derplearning · 14,004
#66
̶с̶а̶м̶̶о̶изолента мёбиуса
@izolenta_mebiusa · 2,775
#67
Институт AIRI
@airi_research_institute · 13,958
#68
Knowledge Accumulator
@knowledge_accumulator · 5,686
#69
То шо нейросети
@toshoseti · 1,391
#70
GPT/ChatGPT/AI Central Александра Горного
@aioftheday · 44,612
#71
Take Friends to Luna Park
@hrlunapark · 20,988
#72
Душный NLP
@stuffyNLP · 6,720
#73
gonzo-обзоры ML статей
@gonzo_ML · 24,684
#74
ML for Value / Ваня Максимов
@ml4value · 5,678
#75
Заметки Computer Vision инженера
@CVML_team · 6,118
#76
Den4ik Research
@den4ikresearch · 1,808
#77
from:adam
@c3po_notes · 6,865
#78
Information Retriever
@inforetriever · 4,161
#79
Reliable ML
@reliable_ml · 6,610
#80
Voice stuff
@voicestuff · 1,818
#81
Нескучный Data Science Jobs
@not_boring_ds_jobs · 9,430
#82
Tensor Banana
@tensorbanana · 2,941
#83
42 секунды
@ftsec · 19,398
#84
(sci)Berloga Всех Наук и Технологий
@sberlogabig · 8,018
#85
Адель и МЛь
@adel_and_ml · 4,117
#86
ODS Events
@datafest · 8,850
#87
rizzearch
@rizzearch · 1,006
#88
TechSparks
@techsparks · 46,765
#89
Data Science Jobs
@datasciencejobs · 22,549
#90
tldr_tany (Таня Савельева)
@tldr_tany · 8,401
#91
Ai molodca
@strangedalle · 47,598
#92
Анализ данных (Data analysis)
@data_analysis_ml · 51,930
#93
Стартап дня. Александр Горный.
@startupoftheday · 62,622
#94
Нейронки и вино
@neural_wine · 1,934
#95
Нейронавт | Нейросети в творчестве
@GreenNeuralRobots · 13,387
#96

Read from Telegram’s recommendation API, most recently 9 September 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.

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.

Сиолошная
@seeallochnaya · 81,058
Telegram ranks this channel #4 of 97 here — alongside 96 others — read 19 August 2026
e/acc
@cryptoEssay · 63,672
Telegram ranks this channel #5 of 96 here — alongside 95 others — read 21 August 2026
эйай ньюз
@ai_newz · 98,249
Telegram ranks this channel #5 of 94 here — alongside 93 others — read 16 August 2026
Kali Novskaya
@rybolos_channel · 19,139
Telegram ranks this channel #7 of 93 here — alongside 92 others — read 4 October 2026
Machinelearning
@ai_machinelearning_big_data · 276,026
Telegram ranks this channel #8 of 95 here — alongside 94 others — read 10 August 2026
Sber AI
@SberAIScience · 26,533
Telegram ranks this channel #10 of 95 here — alongside 94 others — read 10 September 2026
Нейроскептик
@neuroskep · 29,743
Telegram ranks this channel #10 of 90 here — alongside 89 others — read 8 September 2026
Время Валеры
@cryptovalerii · 32,031
Telegram ranks this channel #11 of 94 here — alongside 93 others — read 6 September 2026
Denis Sexy IT 🤖
@denissexy · 140,483
Telegram ranks this channel #12 of 95 here — alongside 94 others — read 13 August 2026
Data Secrets
@data_secrets · 96,013
Telegram ranks this channel #13 of 98 here — alongside 97 others — read 17 August 2026
Силиконовый Мешок
@prompt_design · 92,765
Telegram ranks this channel #15 of 96 here — alongside 95 others — read 18 August 2026
Yandex for ML
@yandexforml · 19,132
Telegram ranks this channel #24 of 96 here — alongside 95 others — read 4 October 2026
АйТиБорода
@itbeard · 19,000
Telegram ranks this channel #27 of 93 here — alongside 92 others — read 3 October 2026
Machine learning Interview
@machinelearning_interview · 30,569
Telegram ranks this channel #27 of 98 here — alongside 97 others — read 7 September 2026
Take Friends to Luna Park
@hrlunapark · 20,988
Telegram ranks this channel #29 of 88 here — alongside 87 others — read 28 September 2026
Data Science | Machinelearning [ru]
@devsp · 19,677
Telegram ranks this channel #31 of 91 here — alongside 90 others — read 30 September 2026
Lama AI
@lama_channel_gpt · 24,085
Telegram ranks this channel #33 of 90 here — alongside 89 others — read 15 September 2026
CyberYozh AI Security
@CyberYozh_AI_security · 26,046
Telegram ranks this channel #34 of 91 here — alongside 90 others — read 12 September 2026
Метаверсище и ИИще
@cgevent · 53,530
Telegram ranks this channel #41 of 92 here — alongside 91 others — read 25 August 2026
Техасский Вестник
@starbasepost · 19,235
Telegram ranks this channel #45 of 92 here — alongside 91 others — read 4 October 2026
gonzo-обзоры ML статей
@gonzo_ML · 24,684
Telegram ranks this channel #47 of 93 here — alongside 92 others — read 16 September 2026
Dev & ML Connectable Jobs
@dev_connectablejobs · 29,061
Telegram ranks this channel #47 of 94 here — alongside 93 others — read 10 September 2026
Ряды Фурье
@Fourier_series · 43,863
Telegram ranks this channel #48 of 93 here — alongside 92 others — read 29 August 2026
Анализ данных (Data analysis)
@data_analysis_ml · 51,930
Telegram ranks this channel #48 of 93 here — alongside 92 others — read 25 August 2026

This channel appears in 45 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 7 November 2026 — this entry's latest reading, not the date you are reading this.

“LLM под капотом” (@llm_under_hood), 30,149 subscribers as measured 7 November 2026. Telegram Register, tgregister.com/channel/llm_under_hood.

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.