🚀 Stage 2 of the SWE MERA Challenge has started! Here's what's new this time: 🔹 Evaluation now runs inside Docker — your model and (optionally) a harness solve the tasks there 🔹 48 tasks in Go, Python, PHP, and one more language, with varying difficulty levels 🔹 We're giving you half of an NVIDIA PRO 6000 to run the models Big thanks to Kazteleport for providing the GPUs for the competition! 🙏 🏆 Reminder: the Top-3 p…

Channel
Data Science by ODS.ai 🦜
@opendatascience
On this record: Topic · Previous handles · Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Citations · Handles named that no longer answer · Telegram's recommendations · Cite this entry
38,200subscribers
-1,010 since we began measuring on 5 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
Register entry
| Telegram ID | -1001004955392 |
|---|---|
| Type | Channel |
| Username | @opendatascience |
| Description | First Telegram Data Science channel. Covering all technical and popular staff about anything related to Data Science: AI, Big Data, Machine Learning, Statistics, general Math and the applications of former. To reach editors contact: @malev |
| Created | 22 September 2015 — measured — cross-checked against a third-party dataset (ext.tg_channel) |
| First recorded | 6 August 2026 |
| Last confirmed live | 24 October 2026 |
| Measurements held | 50 |
| Confirmed unchanged | 1 time, most recently 24 October 2026 |
| On Telegram | t.me/opendatascience |
Topic
Technology — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 20 August 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 why it has no browse page of its own yet.
Previous handles
Recorded in 2019 as “Data Science” — the title held for this same channel (matched by Telegram id, not by handle) in the Pushshift Telegram Dataset, a third-party archive captured in 2019-2020, years before this register made its own first observation. CC BY 4.0, Baumgartner, Zannettou, Squire & Blackburn (2020), Zenodo. A third party’s dated snapshot, not a measurement this register made itself.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 24 Oct 2026, 16:47 | 38,200 | -9 |
| 23 Oct 2026, 19:50 | 38,209 | -21 |
| 22 Oct 2026, 22:15 | 38,230 | -12 |
| 21 Oct 2026, 21:09 | 38,242 | -16 |
| 20 Oct 2026, 14:16 | 38,258 | -17 |
| 19 Oct 2026, 11:42 | 38,275 | -12 |
| 18 Oct 2026, 15:04 | 38,287 | -29 |
| 17 Oct 2026, 11:29 | 38,316 | -4 |
| 16 Oct 2026, 13:28 | 38,320 | -10 |
| 15 Oct 2026, 13:56 | 38,330 | -13 |
| 14 Oct 2026, 14:47 | 38,343 | -22 |
| 13 Oct 2026, 03:10 | 38,365 | -50 |
| 8 Oct 2026, 19:40 | 38,415 | -71 |
| 4 Oct 2026, 09:41 | 38,486 | -140 |
| 25 Sept 2026, 23:22 | 38,626 | -72 |
| 19 Sept 2026, 04:18 | 38,698 | -28 |
| 16 Sept 2026, 20:01 | 38,726 | -13 |
| 14 Sept 2026, 19:37 | 38,739 | -20 |
| 13 Sept 2026, 06:57 | 38,759 | -31 |
| 11 Sept 2026, 09:36 | 38,790 | first reading |
Engagement
60 posts held, back to 14 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 147 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 5.97%
- avg views ÷ 38,200 subscribers
- Avg views / post
- 2,280
- 10 posts measured
- Reaction rate
- 0.272%
- reactions ÷ views · ER floor
- Posts in window
- 10
- of 60 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.
| Window | Rolling 30 days · latest post in window 23 October 2026 |
|---|---|
| Posts held | 60 (14 July 2026 – 23 October 2026) |
| Views total | 22,799 |
| Reactions total | 62 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 24 Oct 2026, 19:55 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
- ≈1,310
- Videos
- ≈152
- Links
- ≈2,320
Lifetime counters from Telegram’s own channel header, read 24 October 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
- Video runtime
- 13m 29s
- Average length
- 2m 42s
Measured directly from 5 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
459 reactions across 52 posts, in 30 distinct kinds. The most used accounts for 26.8% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 123 | 26.8% | |
| ❤ | 115 | 25.1% | |
| 🔥 | 83 | 18.1% | |
| 😁 | 34 | 7.41% | |
| 🤯 | 26 | 5.66% | |
| 🤡 | 25 | 5.45% | |
| 🤷♂ | 7 | 1.53% | |
| 🥱 | 6 | 1.31% | |
| 🤣 | 4 | 0.871% | |
| 👌 | 3 | 0.654% | |
| 🗿 | 3 | 0.654% | |
| 🤓 | 3 | 0.654% | |
| 🤨 | 3 | 0.654% | |
| 🥰 | 3 | 0.654% | |
| 🌚 | 2 | 0.436% | |
| 🎉 | 2 | 0.436% | |
| 💊 | 2 | 0.436% | |
| 🤩 | 2 | 0.436% | |
| 🫡 | 2 | 0.436% | |
| ✍ | 1 | 0.218% | |
| 10 further kinds | 10 | 2.18% |
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 56 of the 60 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 472 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 60 most recent posts we hold, published 14 July 2026 to 23 October 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
- 1
- across the posts below
- Posts paid on
- 1
- of 60 we hold a reading for · 2%
- Most on one post
- 1
- single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @opendatascience. 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 60 most recent posts we hold for this entry, published 14 July 2026 to 23 October 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
🟢 NVIDIA на конференции в Берлине показала весь ИИ: от ноутбука до целой фабрики - https://x.com/nvidia/status/2112854401207439553 💻 Ноутбук. Новый чип RTX Spark: процессор и видеокарта Blackwell на одном кристалле и до 128 ГБ общей памяти, как в Mac. По словам NVIDIA, он выдаёт до 1 петафлопса для ИИ и запускает локально модели до 120 млрд параметров🤙 То есть ИИ-агенты работают прямо на коленях, без облака и подписо…
🤯2
We are starting NOW! https://www.youtube.com/watch?v=6uS0sLDp_iY
🔥1
we are glad to announce that tomorrow 10 am UTC+3 Valentin Malykh and Dmitry Kolodezev will will host an Ask Me Anything session with Zheng Wang - one the main contributors to openJiuwen platform Zheng Wang is also an author of several well-known papers on retrieval augmented generation and agents, if you are interested please join! link for translation
🫡2
Доброе утро! ☀️ Встречайте новый выпуск подкаста "Капитанский мостик". Ведущие Валентин Малых и Дмитрий Колодезев разбирают главные ИИ-события недели: Sakana представила ИИ-ученого, обсуждаем глубокое рецензирование и будущее научных публикаций, вычисления прямо в памяти и китайские успехи в ИИ-математике. Смотрите видео на каналах ⤵️ ODS VK Video ODS YouTube 📩 Присылайте новости для обсуждения в канал "Дата-капита…
🤓3❤1
Всем привет! Встречайте воскресный выпуск подкаста "Капитанский мостик". В этот раз подкаст проводился вживую, как часть программы Data Fest Siberia 7. Ведущие Валентин Малых и Дмитрий Колодезев разбирали главные ИИ-события недели, главная тема — математика, созданная ИИ. Смотрите видео на каналах ⤵️ ODS VK Video ODS YouTube 📩 Присылайте новости для обсуждения в канал "Дата-капитаны" в mattermost (авторизуйтесь чер…
❤2🤩2🤡1😁1
Доброе утро! ☀️ Встречайте новый выпуск подкаста "Капитанский мостик". Ведущие Валентин Малых и Дмитрий Колодезев разбирают главные ИИ-события недели: вышел Gemini 4, Figure косплеит Терминатора, Пентагон закупает беспилотники, а Google несёт вычисления в космос. Смотрите видео на каналах ⤵️ ODS VK Video ODS YouTube 📩 Присылайте новости для обсуждения в канал "Дата-капитаны" в mattermost (авторизуйтесь через ODS.ai…
❤2🎉1👍1🤡1
PewDiePie учил свой ИИ на ответах OpenAI. Получил бан. Обжаловал. Попробовал снова. Ещё бан 🤖 По словам блогера, именно так закончились эксперименты с обучающими данными для Ajax. В показанном им письме OpenAI причиной одной из блокировок названа дистилляция: использование ответов одной модели для обучения другой. Ajax создан на базе Qwen 3.5 9B для Odysseus. Это локальный помощник для повседневных задач: поиска, р…
👍16💊2🤷♂2❤1👌1🔥1🥰1
GOOOGLEEE!!🌈🌈🌈🌈 https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-4-argon/ Google показала Gemini 4 Argon, свою новую флагманскую модель для кода, работы с корпоративными документами и киберзащиты. По тестам самой Google: 77,9% на DeepSWE (реальные задачи по коду), первое место на Vals Index (финансы, право, налоги) и в Zapier AutomationBench, 91,7% на LVBench (длинные видео), аутпут 1 …
🔥11😁2❤1
Доброе утро! ☀️ Представляем Вашему вниманию выпуск подкаста "Капитанский мостик". Ведущие Валентин Малых и Дмитрий Колодезев главные ИИ-события недели: Юрген Шмидхубер в Sakana, биохакеры из Anthropic и суверенная LLM от Яндекса. Смотрите видео на каналах ⤵️ ODS VK Video ODS YouTube 📩 Присылайте новости для обсуждения в канал "Дата-капитаны" в mattermost (авторизуйтесь через ODS.ai).
👍2❤1🤡1
Каждый релиз ллм все больше напоминает апдейт лидерборда на Каггле. Крутого нового уже ничего, фичи подкрутили, памяти добавили, но заруба как была за правильный сид, так и осталася. А как только лидерборд пробьют на 1%, все сразу поймут что сделать чтобы также улучшить решения. Как будто не отличаются они сильно уже не только от своего прошлого поколения, так еще и от конкурентов
👌2👍2👏1
Каждый релиз ллм все больше напоминает выход новых айфонов. Крутого нового уже ничего, камеру подкрутили, памяти добавили, но как был выбор чистой вкусовщиной, так и остался. А проф бенчмарки личные есть только у 0.00001% аудитории. Как будто не отличаются они сильно уже не только от своего прошлого поколения, так еще и от конкурентов
👍4😁4❤1
Showing the 12 most recent of 60 posts we hold for @opendatascience. 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
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Republishes
Channels on the register whose posts this channel has forwarded.
@datafest · 8,86012 postsMachinelearning
@ai_machinelearning_big_data · 277,5898 postsАнализ данных (Data analysis)
@data_analysis_ml · 51,7306 postsFuturis
@Futuris · 6,8345 postsMachine learning Interview
@machinelearning_interview · 30,5582 postsGolang
@Golang_google · 40,5951 postML Underhood
@MLunderhood · 5,0581 postСаша делает стартап
@aimalysheva · 2,0281 postИИзвестия 🤖
@aizvestia · 6701 postBig Data AI
@bigdatai · 18,3711 postChillHouse
@chillhousetech · 6,7241 postМониторинг аналитики об IT
@ict_moscow_analytics · 2,2171 postODS Courses
@odscourses · 3,4231 postDataGym Channel [Power of data]
@powerofdata · 2,4151 postRust
@rust_code · 9,1121 postSilero News
@silero_news · 1,4191 postrandom AI channel name
@slavasmirnov_ch · 2391 postValuable AI / Валентин Малых
@valuableai · 2,4461 post@yegor256 news
@yegor256news · 9,1571 post
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 4 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.
Names
Channels on the register whose handles appear in this channel's posts.
@valuableai · 2,44613 postsMachinelearning
@ai_machinelearning_big_data · 277,5897 postsАнализ данных (Data analysis)
@data_analysis_ml · 51,7302 postsMachine learning Interview
@machinelearning_interview · 30,5582 postsИИзвестия 🤖
@aizvestia · 6701 postBig Data AI
@bigdatai · 18,3711 postFuturis
@Futuris · 6,8341 postGolang
@Golang_google · 40,5951 postIXBT Games | Короче
@ixbtgames · 68,1481 post@levelsio
@levelsio · 3,0511 postСиликоновый Мешок
@prompt_design · 86,9081 postМедоед
@realmedoyed · 541 postRust
@rust_code · 9,1121 post
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.
Handles this channel named that no longer answer
- Dead references
- 1
- handles named in this channel’s posts, vacant today
- Evidenced gone
- 0
- we ourselves saw one of these resolve, at some point
- Never seen alive
- 1
- vacant every time we have ever looked
@opendatascience named 1 handle that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
named in 2 posts, 2 September 2026 – 4 September 2026
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.
@ai_machinelearning_big_data · 277,589
Telegram ranks this channel #28 of 95 here — alongside 94 others — read 10 August 2026
@ieofficial · 65,496
Telegram ranks this channel #38 of 92 here — alongside 91 others — read 21 August 2026
@cloudymlofficial · 46,977
Telegram ranks this channel #57 of 88 here — alongside 87 others — read 26 August 2026
@DeepLearning_ai · 57,214
Telegram ranks this channel #59 of 87 here — alongside 86 others — read 23 August 2026
@Artificial_intelligence_in · 65,843
Telegram ranks this channel #59 of 90 here — alongside 89 others — read 21 August 2026
@computer_science_and_programming · 139,373
Telegram ranks this channel #65 of 87 here — alongside 86 others — read 13 August 2026
@science · 119,900
Telegram ranks this channel #84 of 92 here — alongside 91 others — read 14 August 2026
@ai_newz · 97,711
Telegram ranks this channel #86 of 94 here — alongside 93 others — read 16 August 2026
This channel appears in 8 seed channels' Telegram-generated recommendation lists 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 24 October 2026 — this entry's latest reading, not the date you are reading this.
“Data Science by ODS.ai 🦜” (@opendatascience), 38,200 subscribers as measured 24 October 2026. Telegram Register, tgregister.com/channel/opendatascience.
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.