#ml #systemdesign #interview

Channel
oNLP fans
@oNLPfans
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
36subscribers
+0 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
Register entry
| Telegram ID | -1002898119902 |
|---|---|
| Type | Channel |
| Username | @oNLPfans |
| Description | Про NLP и все что с ними связано |
| Created | Between 1 June 2025 and 30 September 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 10 August 2026 |
| Last confirmed live | 10 August 2026 |
| Measurements held | 2 |
| On Telegram | t.me/oNLPfans |
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 10 Aug 2026, 22:45 | 36 | no change |
| 7 Aug 2026, 19:17 | 36 | first reading |
Engagement
15 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 1 pageof Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 102.8%
- avg views ÷ 36 subscribers
- Avg views / post
- 37.0
- 10 posts measured
- Reaction rate
- 16.3%
- reactions ÷ views · ER floor
- Posts in window
- 10
- of 15 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. It is computed over the 9 of 10 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 8 August 2026 |
|---|---|
| Posts held | 15 (7 July 2026 – 8 August 2026) |
| Views total | 370 |
| Reactions total | 58 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 10 Aug 2026, 22:45 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
- 43
- Videos
- 2
- Links
- 21
Lifetime counters from Telegram’s own channel header, read 10 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
- Video runtime
- 47s
- Average length
- 47s
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
79 reactions across 14 posts, in 15 distinct kinds. The most used accounts for 26.6% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 🔥 | 21 | 26.6% | |
| 🤯 | 12 | 15.2% | |
| 🍌 | 8 | 10.1% | |
| 😁 | 8 | 10.1% | |
| 🤩 | 7 | 8.86% | |
| ❤🔥 | 5 | 6.33% | |
| 💅 | 4 | 5.06% | |
| 🏆 | 3 | 3.80% | |
| 🐳 | 2 | 2.53% | |
| 💯 | 2 | 2.53% | |
| 😭 | 2 | 2.53% | |
| 🤔 | 2 | 2.53% | |
| ❤ | 1 | 1.27% | |
| 🥱 | 1 | 1.27% | |
| 🥴 | 1 | 1.27% |
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 14 of the 15 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 79reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 15 most recent posts we hold, published 7 July 2026 to 8 August 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
Топ-15 сайтов для подготовке к собесу, когда до него осталось три дня😎 Сейчас очень много подборок ресурсов по подготовке к собесам, но часто, когда времени мало, ты не успеваешь пройти все темы. Поэтому ниже я подготовил свой топ-ресурсов, который будет полезен каждому: 1. Когда сказали, что на кодинге будет мл задачи 2. Быстрые вопросы про LLM и docker в виде карточек 3. Архитектура AI-агентов, когда нужно выделит…
❤🔥3🔥1
Курс по Visual GenAI от Yandex Research и ШАД Авторы CV Time не только пишут обзоры статей о компьютерном зрении, но и создают обучающие курсы. Сегодня делимся курсом ШАДа «Генеративные модели в компьютерном зрении», который ведёт Дмитрий Баранчук, руководитель группы GenAI в Yandex Research, вместе с праймовой командой исследователей в этой области. Будет полезно тем, у кого есть базовые знания по генеративкам и …
🔥2🤔2🍌1
Последнее время я совсем разленился читать сырые статьи😶, поэтому сгенерировал курсик по модельке и данным выше🤥 Пользуйтесь наслаждайтесь🌷😚
🍌2💅2🔥1
https://huggingface.co/nvidia/NVIDIA-NemotronLabs-VoiceChat-11B NVIDIA NemotronLabs VoiceChat is a 11B end-to-end, real-time speech full duplex (FD) model for conversational AI that jointly performs streaming speech understanding and speech generation [1, 2]. Unlike traditional cascaded stacks (ASR → LLM → TTS), this model achieves full duplex, real-time, seamless voice interaction in one unified architecture, elimi…
🤯3🍌2🔥1
OpenAI сбросили цены на GPT 5.6 Luna теперь дешевле в пять раз, всего $0.2/$1.2 за миллион токенов, против $1/$6 на релизе. Цену Terra сбросили на 20%, до $2/$12 за миллион токенов. Понижение цен касается не только API, но и квоты в Codex/ChatGPT Work. Sol не получил понижения цены, но для него выпустили Fast режим, который в 2.5x быстрее по 2x цене, но про дату релиза Sol запущенного на железе Cerebras OpenAI всё е…
🤩4🔥2💅1
Photo, posted without a caption
🍌3💯2
Photo, posted without a caption
😁5🐳2😭2
Вышел Opus 5, уже доступен в Claude Code и на сайте. Модель во многом... лучше Fable 5 😎 Даже на Frontier-Bench, про который я писал сегодня — уже +9%. В общем выглядит как новая рабочая лошадка, постараюсь погонять в ближайший месяц и в хвост и в гриву. Цена та же, Fast-режим тоже есть. Карточка модели Ограничения будут как у Opus 4.8 (не как у Fable 5), с исключением в кибербезопасности. Это означает, что относ…
🤯4🔥2🥱1
🏆 Первое место на хакатоне «Цифровое здоровье» Недавно прошёл онлайн-хакатон «Цифровое здоровье», где мы с командой itmoni заняли первое место в одной из задач. Хакатон был посвящён ИИ в онкологии. Его проводили НМИЦ онкологии им. Н.Н. Петрова и Центр научной коммуникации ИТМО при поддержке Центра технологий для общества Yandex Cloud. Все задачи сформулировали практикующие врачи на основе реальных рабочих процессов.…
🔥5🏆3❤🔥2
Guided Star-Shaped Masked Diffusion У masked diffusion LLM есть довольно тупая проблема: если токен уже размаскировался, всё, он заморожен. Ошиблась модель на раннем шаге — дальше она уже не исправляет ошибку, а пытается построить вокруг неё текст. Такие несогласованности особенно заметны при маленьком количестве шагов. Существующие методы перемаскирования дают модели шанс передумать, но требуют сотен шагов, что уби…
🔥4
Новый сценарий от авторов AI-2027 https://ai-2040.com Бегом читать
🤯3❤1
Showing the 12 most recent of 15 posts we hold for @oNLPfans. 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
Republishes
Channels on the register whose posts this channel has forwarded.
@ai_newz · 95,7972 postsСиолошная
@seeallochnaya · 77,4592 postsеба́ные идеи для резерча
@ebaresearch · 5,2611 postML Baldini • Nikita Boyandin
@ml_baldini · 1,6141 postКПД
@quant_prune_distill · 3,4281 postquant barbie
@quantbarbie · 1,5731 postSpeech Technology
@speechtech · 1,6891 postCV Time
@timeforcv · 3,3601 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
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.
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 August 2026 — this entry's latest reading, not the date you are reading this.
“oNLP fans” (@oNLPfans), 36 subscribers as measured 10 August 2026. Telegram Register, tgregister.com/channel/oNLPfans.
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.