Claude решил задачу по физике чёрных дыр, которую не могли закрыть около 20 лет Anthropic опубликовала исследование, в котором внутренняя исследовательская модель Claude получила новый результат в теоретической физике. Работа посвящена переходу Хокинга - Пейджа. Это фазовый переход, связанный с термодинамикой чёрных дыр в пространстве анти-де Ситтера (AdS). Исследователей интересовал вопрос: сохраняется ли этот пе…

Channel
Data Science
@datascienceiot
On this record: Topic · Growth · Engagement · What this channel posts · Advertising · Posts · Posts recorded as deleted · Citations · Handles named that no longer answer · Telegram's recommendations · Cite this entry
42,496subscribers
+254 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 | 10 November 2026 |
| Measurements held | 62 |
| Confirmed unchanged | 1 time, most recently 10 November 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 the other topics.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 10 Nov 2026, 08:51 | 42,496 | -17 |
| 8 Nov 2026, 19:20 | 42,513 | -17 |
| 7 Nov 2026, 11:21 | 42,530 | -10 |
| 6 Nov 2026, 10:39 | 42,540 | -9 |
| 5 Nov 2026, 10:07 | 42,549 | -1 |
| 4 Nov 2026, 07:26 | 42,550 | -18 |
| 3 Nov 2026, 05:29 | 42,568 | -7 |
| 2 Nov 2026, 03:21 | 42,575 | -7 |
| 1 Nov 2026, 00:16 | 42,582 | -4 |
| 30 Oct 2026, 03:19 | 42,586 | -6 |
| 28 Oct 2026, 23:55 | 42,592 | -12 |
| 27 Oct 2026, 23:55 | 42,604 | -21 |
| 27 Oct 2026, 00:09 | 42,625 | -11 |
| 25 Oct 2026, 21:01 | 42,636 | -5 |
| 24 Oct 2026, 21:50 | 42,641 | -8 |
| 23 Oct 2026, 20:28 | 42,649 | +3 |
| 22 Oct 2026, 21:19 | 42,646 | +17 |
| 21 Oct 2026, 14:37 | 42,629 | +73 |
| 20 Oct 2026, 13:16 | 42,556 | +9 |
| 18 Oct 2026, 19:26 | 42,547 | first reading |
Engagement
81 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 194 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 6.10%
- avg views ÷ 42,496 subscribers
- Avg views / post
- 2,590
- 19 posts measured
- Reaction rate
- —
- this channel exposes no reaction counts
- Posts in window
- 19
- of 81 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 10 November 2026 |
|---|---|
| Posts held | 81 (7 July 2026 – 10 November 2026) |
| Views total | 49,280 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 10 Nov 2026, 22:41 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
- ≈1,790
- Videos
- ≈5
- Links
- ≈2,180
Lifetime counters from Telegram’s own channel header, read 10 November 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
- 1m 04s
- Average length
- 32s
Measured directly from 2 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.
Advertising
- Ad load
- 9.88%
- 8 of 81 posts carry an ad marker
- Regulatory tokens
- 8
- posts carrying an erid · 8 distinct tokens
- Median views · ads
- 3,020
- over 8 measured posts
- Median views · rest
- 3,450
- over 73 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 |
| 2VtzqvCaFkz | 1 | 10 November 2026 | 10 November 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 |
| 2W5zFGXZQLy | 1 | 7 October 2026 | 7 October 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 81 most recent posts we hold, published 7 July 2026 to 10 November 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
Telegram’s own ‘edited’ marker: 1 of 19 posts held from the last 30 days (5.26%) 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).
🔍 Открытое ML-собеседование с техлидом Яндекса| 12 ноября, 19:00 мск Приходи онлайн посмотреть, как проходит техническое интервью на ML-инженера, и попробуй ответить на вопросы вместе с кандидатом Как всё будет проходить: 📂 Интервьюер: Любовь Чубарова, техлид в Яндексе (RnD Alice AI), одна из первых сотрудниц YandexArt, преподаватель ВШЭ, экс-руководитель аналитики Центра ИИ Сколтеха. В роли кандидата – инженер-до…
Yoshua Bengio and collaborators just released a goldmine 182-page survey on mechanistic interpretability! "Understanding AI from the Inside" 📓 Read @datascienceiot
A Circuit for In-Context Learning 📓 Read @datascienceiot
Алгоритм знает, где вы будете 7-го ноября 😎 RecSys-митап в Москве для тех, кто уже строит рекомендательные системы и хочет делать это еще лучше. В программе — доклады от топовых экспертов Сбера с разбором кейсов, свежих подходов и неочевидных решений. После официальной части — нетворкинг. Время в узком кругу профессионалов и сообщества Зеленый RecSys. Участие бесплатное, но количество мест ограничено. Москва. Су…
Mistral Large 4 📓 Read @datascienceiot
"Large Flow Language Models" What if we could turn existing LLMs into diffusionLMs that generate multiple tokens in parallel without losing accuracy? 📓 Read @datascienceiot
Бесплатная книга о больших языковых моделях – 315 страниц от предобучения до рассуждений. Foundations of Large Language Models Тун Сяо и Цзинбо Чжу системно объясняет, как устроены LLM, как их обучают и применяют. Внутри шесть основных тем: - Предобучение: задачи обучения и архитектуры моделей. - Генеративные модели: Transformer, подготовка данных, масштабирование и длинный контекст. - Промптинг: обучение на приме…
Working with Agentic `Teammates': When a New Organizational Actor Collides with the Human Ecosystem of Work 📓 Read @datascienceiot
The Geometry of Agent Memory: Forecasting Retrieval-Bound Memory Failures, and Characterizing Its Limits 📓 Read @datascienceiot
At the Limits of Computability: Steps Towards Autonomous AI Discovery on the Busy Beaver Frontier 📓 Read @datascienceiot
Patch the Planet: global response coordination as agents uncover critical vulnerabilities https://openai.com/index/coordinated-disclosure-of-critical-vulnerabilities/ @datascienceiot
Showing the 12 most recent of 81 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.
Posts recorded as deleted after publishing
We recorded 8 posts on @datascienceiot as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
- First seen missing
- 21 August 2026
- Most recent seen missing
- 3 November 2026
- Median time before seen missing
- 8 days
- Seen missing in the last 30 days
- 2
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 5 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 · 275,6594 postsAndroid разработка
@android_its · 4,8613 postsBig Data AI
@bigdatai · 18,3293 postsC++ Academy
@cpluspluc · 15,4573 postsАнализ данных (Data analysis)
@data_analysis_ml · 51,9233 postsМатематика Дата саентиста
@data_math · 14,4193 postsDevOps
@DevOPSitsec · 23,8923 postsАнглийский для программистов
@english_forprogrammers · 8,2373 postsGameDev Pulse
@GameDEV · 4,3663 postsGolang
@Golang_google · 40,4533 postsHaskell
@haskell_tg · 5903 postsJavascript
@javascriptv · 16,6643 postsLinux Academy
@linuxacademiya · 28,6473 postsKali Linux
@linuxkalii · 55,8423 postsMachine learning Interview
@machinelearning_interview · 30,5603 postsIT мемы | Мемы программиста
@memes_prog · 6,2203 postsМобильная разработка
@mobdevelop · 3,8413 postsPHP Academy
@phpshka · 9,1313 postsPython вопросы с собеседований
@python_job_interview · 24,9063 postsPython/ django
@pythonl · 58,2873 postsReact JS
@react_tg · 16,0493 postsRust
@rust_code · 9,1523 postsData Science. SQL hub
@sqlhub · 36,0253 postsИскусственный интеллект. Высокие технологии
@vistehno · 70,1393 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 12 posts, 8 August 2026 – 31 October 2026
named in 12 posts, 8 August 2026 – 31 October 2026
named in 12 posts, 8 August 2026 – 31 October 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 · 275,659#1
@machinelearning_books · 16,955#2
@data_analysis_ml · 51,923#3
@data_math · 14,419#4
@pythonl · 58,287#5
@machinelearning_interview · 30,560#6
@bigdatai · 18,329#7
@machinelearning_ru · 18,339#8
@ArtificialIntelligencedl · 16,815#9
@data_secrets · 96,035#10
@sqlhub · 36,025#11
@python_job_interview · 24,906#12
@dataanlitics · 6,386#13
@devsp · 19,659#14
@datascienceml_jobs · 21,642#15
@neural · 11,724#16
@deep_school · 10,723#17
@vistehno · 70,139#18
@dsproglib · 18,290#19
@java_library · 14,048#20
@maschinelearning · 10,849#21
@cpluscsharp · 10,015#22
@golang_books · 16,863#23
@physics_lib · 146,676#24
@datajob · 15,139#25
@computer_science_and_programming · 138,623#26
@pro_python_code · 12,302#27
@yandexforml · 19,136#28
@not_boring_ds · 12,081#29
@cryptovalerii · 32,082#30
@MachineLearning9 · 41,912#31
@ds_interview_lib · 4,459#32
@bzd_channel · 36,213#33
@ds_problems_lib · 3,966#34
@odsjobs · 14,582#35
@denissexy · 140,753#36
@cpluspluc · 15,457#37
@dealerAI · 17,113#38
@datasciencefun · 77,697#39
@hahacker_news · 25,231#40
@CodeProgrammer · 68,478#41
@python_djangojobs · 15,125#42
@rockyourdata · 23,685#43
@airi_research_institute · 13,977#44
@datasciencejobs · 22,587#45
@PaperNexus · 34,361#46
@datasciencefree · 68,644#47
@Django_pythonl · 6,573#48
@pythonspecialist · 56,410#49
@start_ds · 11,463#50
@datasfrog · 1,829#51
@data_science_winners · 3,366#52
@datafeeling · 14,208#53
@ds_wiki · 3,183#54
@j_links · 6,943#55
@ML_secrets · 7,365#56
@pyproglib · 36,972#57
@proglibrary · 77,612#58
@zheltyi_ai · 9,371#59
@rust_code · 9,152#60
@DeepLearning_ai · 56,955#61
@ai_newz · 98,262#62
@DevOPSitsec · 23,892#63
@Golang_google · 40,453#64
@seeallochnaya · 81,254#65
@tech_priestess · 15,110#66
@pythonRe · 40,901#67
@Artificial_intelligence_in · 65,715#68
@doomgrad · 8,840#69
@linuxkalii · 55,842#70
@new_yorko_times · 10,720#71
@DataAnalyticsX · 30,880#72
@phpshka · 9,131#73
@llm_under_hood · 30,219#74
@dl_stories · 15,546#75
@rybolos_channel · 19,136#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 · 146,676
Telegram ranks this channel #6 of 72 here — alongside 71 others — read 13 August 2026
@dataflair · 18,577
Telegram ranks this channel #7 of 83 here — alongside 82 others — read 4 October 2026
@pythonl · 58,287
Telegram ranks this channel #7 of 84 here — alongside 83 others — read 22 August 2026
@computer_science_and_programming · 138,623
Telegram ranks this channel #7 of 87 here — alongside 86 others — read 13 August 2026
@devsp · 19,659
Telegram ranks this channel #10 of 91 here — alongside 90 others — read 30 September 2026
@data_analysis_ml · 51,923
Telegram ranks this channel #10 of 93 here — alongside 92 others — read 25 August 2026
@vistehno · 70,139
Telegram ranks this channel #10 of 94 here — alongside 93 others — read 20 August 2026
@sqlhub · 36,025
Telegram ranks this channel #11 of 87 here — alongside 86 others — read 2 September 2026
@python_job_interview · 24,906
Telegram ranks this channel #15 of 90 here — alongside 89 others — read 15 September 2026
@ai_machinelearning_big_data · 275,659
Telegram ranks this channel #17 of 95 here — alongside 94 others — read 10 August 2026
@pythonbooks · 38,331
Telegram ranks this channel #19 of 65 here — alongside 64 others — read 17 September 2026
@MachineLearning9 · 41,912
Telegram ranks this channel #23 of 79 here — alongside 78 others — read 30 August 2026
@datascienceml_jobs · 21,642
Telegram ranks this channel #25 of 97 here — alongside 96 others — read 24 September 2026
@DeepLearning_ai · 56,955
Telegram ranks this channel #25 of 87 here — alongside 86 others — read 23 August 2026
@CodeProgrammer · 68,478
Telegram ranks this channel #30 of 84 here — alongside 83 others — read 20 August 2026
@machinelearning_interview · 30,560
Telegram ranks this channel #31 of 98 here — alongside 97 others — read 7 September 2026
@ml_ds_ai_jobs · 25,720
Telegram ranks this channel #33 of 81 here — alongside 80 others — read 13 September 2026
@PaperNexus · 34,361
Telegram ranks this channel #33 of 85 here — alongside 84 others — read 4 September 2026
@bigdataspecialist · 26,239
Telegram ranks this channel #37 of 80 here — alongside 79 others — read 12 September 2026
@datasciencefree · 68,644
Telegram ranks this channel #43 of 88 here — alongside 87 others — read 20 August 2026
@DataPortfolio · 37,776
Telegram ranks this channel #45 of 83 here — alongside 82 others — read 31 August 2026
@pythonspecialist · 56,410
Telegram ranks this channel #45 of 89 here — alongside 88 others — read 23 August 2026
@pythonadvisorai · 31,362
Telegram ranks this channel #46 of 71 here — alongside 70 others — read 5 September 2026
@pythonist_ru · 23,873
Telegram ranks this channel #48 of 82 here — alongside 81 others — read 17 September 2026
This channel appears in 47 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 10 November 2026 — this entry's latest reading, not the date you are reading this.
“Data Science” (@datascienceiot), 42,496 subscribers as measured 10 November 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.