New Stanford+Together AI paper shows teams that learn to check each other's work solve problems none of them got right alone. 📘 Paper @datascienceiot

Channel
Data Science
@datascienceiot
On this record: Topic · Growth · Engagement · What this channel posts · Advertising · Posts · Citations · Handles named that no longer answer · Telegram's recommendations · Cite this entry
42,634subscribers
+392 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
Register entry
| Telegram ID | -1001131189982 |
|---|---|
| Type | Channel |
| Username | @datascienceiot |
| Description | DS По всем вопросам- @haarrp @ai_machinelearning_big_data - machine learning @pythonl - Python @itchannels_telegram - 🔥 best it channels @ArtificialIntelligencedl - AI @pythonlbooks-📚 @programming_books_it -📚 Реестр РКН: https://clck.ru/3Fk3zS |
| Created | 26 July 2017 — measured — cross-checked against a third-party dataset (TGDataset) |
| First recorded | 6 August 2026 |
| Last confirmed live | 26 September 2026 |
| Measurements held | 35 |
| Confirmed unchanged | 1 time, most recently 26 September 2026 |
| On Telegram | t.me/datascienceiot |
Topic
Education — 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 9 September 2026 and assigned it the closest of 31 fixed categories, at 95% 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.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 26 Sept 2026, 04:55 | 42,634 | -8 |
| 19 Sept 2026, 07:21 | 42,642 | +2 |
| 16 Sept 2026, 22:21 | 42,640 | -15 |
| 15 Sept 2026, 00:19 | 42,655 | +29 |
| 13 Sept 2026, 10:58 | 42,626 | +15 |
| 11 Sept 2026, 15:16 | 42,611 | +14 |
| 8 Sept 2026, 22:38 | 42,597 | +44 |
| 5 Sept 2026, 15:19 | 42,553 | -1 |
| 3 Sept 2026, 19:35 | 42,554 | +17 |
| 2 Sept 2026, 09:52 | 42,537 | +14 |
| 1 Sept 2026, 08:03 | 42,523 | +5 |
| 31 Aug 2026, 06:27 | 42,518 | -1 |
| 30 Aug 2026, 06:27 | 42,519 | +25 |
| 29 Aug 2026, 06:12 | 42,494 | +2 |
| 28 Aug 2026, 06:05 | 42,492 | +1 |
| 27 Aug 2026, 05:11 | 42,491 | -2 |
| 26 Aug 2026, 05:08 | 42,493 | -17 |
| 25 Aug 2026, 02:03 | 42,510 | -8 |
| 23 Aug 2026, 16:06 | 42,518 | +26 |
| 21 Aug 2026, 23:58 | 42,492 | first reading |
Engagement
50 posts held, back to 7 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 102 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 6.60%
- avg views ÷ 42,634 subscribers
- Avg views / post
- 2,810
- 17 posts measured
- Reaction rate
- —
- this channel exposes no reaction counts
- Posts in window
- 17
- of 50 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 25 September 2026 |
|---|---|
| Posts held | 50 (7 July 2026 – 25 September 2026) |
| Views total | 47,840 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 27 Sept 2026, 00:35 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
- ≈1,770
- Videos
- ≈5
- Links
- ≈2,160
Lifetime counters from Telegram’s own channel header, read 27 September 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
- 15s
- Average length
- 15s
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.
Advertising
- Ad load
- 14.0%
- 7 of 50 posts carry an ad marker
- Regulatory tokens
- 7
- posts carrying an erid · 7 distinct tokens
- Median views · ads
- 3,370
- over 7 measured posts
- Median views · rest
- 4,370
- over 43 measured posts
An ad marker, not a judgement about a post. A post is counted here because it carries one of two explicit markings: an erid token, which Russian law has required on paid placements since 2022 and which is issued against a specific advertising contract, or a #реклама / #ad hashtag in the body, which is the channel declaring it itself. The first is documentary; the second is a self-declaration and is weaker. No classifier reads the text and decides — nothing on this site guesses that a post is an advertisement.
This is a floor, and it can only ever be a floor. A channel that runs paid placements without marking them produces no marker for us to count, and an unmarked ad is indistinguishable from an ordinary post on the public surface. The ad load above therefore means “the share of posts that declared themselves”, never “the share of posts that were paid for”. A low figure is not evidence of a channel that runs few ads.
Both figures are medians, and no ratio between them is published. Each is a view reading that actually occurred on a post, picked by percentile_disc rather than averaged, so one viral post cannot move it and no interpolated value is invented between two readings. They are printed side by side with the count behind each rather than as a ratio: an ad and an ordinary post are not otherwise matched — for topic, for length, for hour of day — so the gap between them is a description of two groups and not the effect of one being an ad.
| erid | Posts | First seen | Last seen |
|---|---|---|---|
| 2SDnjezu8Km | 1 | 21 September 2026 | 21 September 2026 |
| 2VSb5weurkr | 1 | 24 September 2026 | 24 September 2026 |
| 2VtzqxCfpUj | 1 | 21 August 2026 | 21 August 2026 |
| 2VtzqxQZmyv | 1 | 25 September 2026 | 25 September 2026 |
| 2W5zFGRNGWm | 1 | 16 July 2026 | 16 July 2026 |
| 2W5zFHVnrdo | 1 | 7 September 2026 | 7 September 2026 |
| 2W5zFJwEKww | 1 | 18 August 2026 | 18 August 2026 |
A token repeated across several posts is one advertising contract placed more than once, which is what the identifier is for. The strings are reproduced exactly as they appeared in the post or in its click-through URL and are not validated against any registry — we record the marker a channel published, and whether it resolves to a real contract is a question for the register that issued it.
Measured over the 50 most recent posts we hold, published 7 July 2026 to 25 September 2026. Views are the latest single reading held for each post, and any reading at or above 1,000 is rounded by Telegram to three significant figures.
Recent posts
Avito DS Meetup: RL, AI-агенты и BidCorrection 🚀 🔸 Булат Шарипов расскажет, как в Авито обучают собственные языковые модели с помощью RL, а Владислав Воробьев — как BidCorrection меняет состав трафика, не трогая сами объявления. 🔸 Всеволод Викулин расскажет, как реально автоматизировать процессы с помощью AI-агентов, — этим и многим другим он поделится на Avito DS Meetup 7 октября. После докладов будет нетворкинг …
Agent Memory Is a Surface for Endogenous Authorization Laundering 📘 Paper @datascienceiot
Участвуй во всероссийском ИТ-чемпионате МТС True Tech Champ 2026 c призовой фондом 10 250 000 рублей. Если тебе нравятся алгоритмы, структуры данных и задачи на чистую логику — участвуй в алгоритмическом треке с индивидуальным зачетом. Решай задачи разного уровня сложности: от базовых до тех, что проверяют скорость мышления и умение оптимизировать решения за ограниченное время. В финале лучшие 120 участников алгор…
Physics-based Deep Learning: Combining Deep Learning with Physical Simulations 📘 Paper @datascienceiot
🔥 DataLens Platform: что происходит, когда data stack собирают в одну систему Yandex B2B Tech представила платформу, которая объединяет хранение, обработку, визуализацию и ИИ-аналитику данных. Вместо связки из нескольких инструментов данные можно обрабатывать и анализировать в единой среде. Встроенный ИИ-помощник принимает запросы на обычном языке и помогает получать показатели без ручной сборки отчётов. Отдельно …
Regularized Recursive Self-Improvement of Agent Harnesses 📘 Paper @datascienceiot
ττ-bench treats agent building like a real client job. 📘 Paper @datascienceiot
Не отставайте от рынка — учитесь со скидкой 16% Если чувствуете, что стоите на месте, и хотите освоить востребованную профессию, — сейчас хороший момент начать. Потому что до 30 сентября на все курсы Практикума действует скидка 16%. Выбрать курс Вы сможете: — получить актуальные навыки; — освоить ИИ-инструменты для работы; — перенять опыт экспертов, которые двигают индустрию; — попасть в сообщество выпускников…
Thinking with Looped Flows 📘 Paper @datascienceiot
📘 Hidden Markov Models (HMM) Короткий материал от Stanford по одной из классических моделей машинного обучения для работы с последовательностями. Внутри разбираются: - состояния и наблюдения - transition и emission probabilities - вычисление вероятности последовательности - декодирование скрытых состояний - обучение параметров HMM - применение к последовательным данным Хороший компактный материал, если нужно быст…
Banger report from Microsoft. They introduce a 4B coding agent trained on roughly 1,500 software engineering environments. 📘 Paper @datascienceiot
Showing the 12 most recent of 50 posts we hold for @datascienceiot. 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.
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 3 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.
@ai_machinelearning_big_data · 279,4172 postsAndroid разработка
@android_its · 4,8802 postsBig Data AI
@bigdatai · 18,2012 postsC++ Academy
@cpluspluc · 15,5362 postsC# 1001 notes
@csharp_1001_notes · 6,6512 postsАнализ данных (Data analysis)
@data_analysis_ml · 50,6562 postsМатематика Дата саентиста
@data_math · 14,2782 postsDevOps
@DevOPSitsec · 23,6842 postsGameDev Pulse
@GameDEV · 4,2672 postsGolang
@Golang_google · 40,4612 postsHaskell
@haskell_tg · 5852 postsJavascript
@javascriptv · 17,0642 postsLinux Academy
@linuxacademiya · 28,4342 postsKali Linux
@linuxkalii · 55,4122 postsMachine learning Interview
@machinelearning_interview · 30,3082 postsIT мемы | Мемы программиста
@memes_prog · 6,2622 postsМобильная разработка
@mobdevelop · 3,8822 postsPHP Academy
@phpshka · 9,2452 postsPython вопросы с собеседований
@python_job_interview · 24,8812 postsPython/ django
@pythonl · 58,8662 postsReact JS
@react_tg · 16,2792 postsRust
@rust_code · 8,8702 postsData Science. SQL hub
@sqlhub · 35,9602 postsИскусственный интеллект. Высокие технологии
@vistehno · 71,4912 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.
Handles this channel named that no longer answer
- Dead references
- 3
- 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
- 3
- vacant every time we have ever looked
@datascienceiot named 3 handles 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 9 posts, 8 August 2026 – 4 September 2026
named in 9 posts, 8 August 2026 – 4 September 2026
named in 9 posts, 8 August 2026 – 4 September 2026
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.
@ai_machinelearning_big_data · 279,417#1
@machinelearning_books · 16,878#2
@data_analysis_ml · 50,656#3
@data_math · 14,278#4
@pythonl · 58,866#5
@machinelearning_interview · 30,308#6
@bigdatai · 18,201#7
@machinelearning_ru · 18,195#8
@ArtificialIntelligencedl · 16,775#9
@data_secrets · 94,138#10
@sqlhub · 35,960#11
@python_job_interview · 24,881#12
@dataanlitics · 6,253#13
@devsp · 19,825#14
@datascienceml_jobs · 21,227#15
@neural · 11,595#16
@deep_school · 10,738#17
@vistehno · 71,491#18
@dsproglib · 18,339#19
@java_library · 14,222#20
@maschinelearning · 10,823#21
@cpluscsharp · 10,067#22
@golang_books · 16,949#23
@physics_lib · 146,712#24
@datajob · 14,830#25
@computer_science_and_programming · 140,074#26
@pro_python_code · 12,361#27
@yandexforml · 18,854#28
@not_boring_ds · 12,052#29
@cryptovalerii · 30,808#30
@MachineLearning9 · 41,424#31
@ds_interview_lib · 4,466#32
@bzd_channel · 36,430#33
@ds_problems_lib · 3,988#34
@odsjobs · 14,059#35
@denissexy · 137,325#36
@cpluspluc · 15,536#37
@dealerAI · 16,667#38
@datasciencefun · 77,580#39
@hahacker_news · 25,571#40
@CodeProgrammer · 68,301#41
@python_djangojobs · 14,786#42
@rockyourdata · 23,732#43
@airi_research_institute · 13,654#44
@datasciencejobs · 22,137#45
@PaperNexus · 33,858#46
@datasciencefree · 68,434#47
@Django_pythonl · 6,611#48
@pythonspecialist · 56,321#49
@start_ds · 11,495#50
@datasfrog · 1,859#51
@data_science_winners · 3,370#52
@datafeeling · 14,242#53
@ds_wiki · 3,209#54
@j_links · 6,904#55
@ML_secrets · 7,398#56
@pyproglib · 37,384#57
@proglibrary · 78,288#58
@zheltyi_ai · 9,387#59
@rust_code · 8,870#60
@DeepLearning_ai · 57,432#61
@ai_newz · 96,889#62
@DevOPSitsec · 23,684#63
@Golang_google · 40,461#64
@seeallochnaya · 79,594#65
@tech_priestess · 14,890#66
@pythonRe · 40,364#67
@Artificial_intelligence_in · 65,766#68
@doomgrad · 8,800#69
@linuxkalii · 55,412#70
@new_yorko_times · 10,554#71
@DataAnalyticsX · 30,208#72
@phpshka · 9,245#73
@llm_under_hood · 29,146#74
@dl_stories · 15,572#75
@rybolos_channel · 19,011#76
Read from Telegram’s recommendation API, most recently 29 August 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.
@physics_lib · 146,712
Telegram ranks this channel #6 of 72 here — alongside 71 others — read 13 August 2026
@pythonl · 58,866
Telegram ranks this channel #7 of 84 here — alongside 83 others — read 22 August 2026
@computer_science_and_programming · 140,074
Telegram ranks this channel #7 of 87 here — alongside 86 others — read 13 August 2026
@data_analysis_ml · 50,656
Telegram ranks this channel #10 of 93 here — alongside 92 others — read 25 August 2026
@vistehno · 71,491
Telegram ranks this channel #10 of 94 here — alongside 93 others — read 20 August 2026
@sqlhub · 35,960
Telegram ranks this channel #11 of 87 here — alongside 86 others — read 2 September 2026
@python_job_interview · 24,881
Telegram ranks this channel #15 of 90 here — alongside 89 others — read 15 September 2026
@ai_machinelearning_big_data · 279,417
Telegram ranks this channel #17 of 95 here — alongside 94 others — read 10 August 2026
@pythonbooks · 38,517
Telegram ranks this channel #19 of 65 here — alongside 64 others — read 17 September 2026
@MachineLearning9 · 41,424
Telegram ranks this channel #23 of 79 here — alongside 78 others — read 30 August 2026
@datascienceml_jobs · 21,227
Telegram ranks this channel #25 of 97 here — alongside 96 others — read 24 September 2026
@DeepLearning_ai · 57,432
Telegram ranks this channel #25 of 87 here — alongside 86 others — read 23 August 2026
@CodeProgrammer · 68,301
Telegram ranks this channel #30 of 84 here — alongside 83 others — read 20 August 2026
@machinelearning_interview · 30,308
Telegram ranks this channel #31 of 98 here — alongside 97 others — read 7 September 2026
@ml_ds_ai_jobs · 25,932
Telegram ranks this channel #33 of 81 here — alongside 80 others — read 13 September 2026
@PaperNexus · 33,858
Telegram ranks this channel #33 of 85 here — alongside 84 others — read 4 September 2026
@bigdataspecialist · 26,486
Telegram ranks this channel #37 of 80 here — alongside 79 others — read 12 September 2026
@datasciencefree · 68,434
Telegram ranks this channel #43 of 88 here — alongside 87 others — read 20 August 2026
@DataPortfolio · 38,028
Telegram ranks this channel #45 of 83 here — alongside 82 others — read 31 August 2026
@pythonspecialist · 56,321
Telegram ranks this channel #45 of 89 here — alongside 88 others — read 23 August 2026
@pythonadvisorai · 32,027
Telegram ranks this channel #46 of 71 here — alongside 70 others — read 5 September 2026
@pythonist_ru · 24,046
Telegram ranks this channel #48 of 82 here — alongside 81 others — read 17 September 2026
@datasciencefun · 77,580
Telegram ranks this channel #48 of 85 here — alongside 84 others — read 19 August 2026
@analytics_secrets · 46,900
Telegram ranks this channel #49 of 85 here — alongside 84 others — read 27 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 26 September 2026 — this entry's latest reading, not the date you are reading this.
“Data Science” (@datascienceiot), 42,634 subscribers as measured 26 September 2026. Telegram Register, tgregister.com/channel/datascienceiot.
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.