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Channel

Частные заметки одного лица

@sl_notes

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry

261subscribers

+0 since we began measuring on 24 September 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1001220972834
TypeChannel
Username@sl_notes
DescriptionСтатейки, мысли, заметки @shiryaeff
CreatedBetween 1 March 2018 and 31 August 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded24 September 2026
Last confirmed live24 September 2026
Measurements held2
On Telegramt.me/sl_notes

Growth

26124 Sept 2026, 21:47 — 261 subscribers24 Sept 2026, 22:22 — 261 subscribers24 Sept 2026, 21:4724 Sept 2026, 22:22
2 measurements taken within a single day. 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 260–262 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
24 Sept 2026, 22:22261no change
24 Sept 2026, 21:47261first reading

Engagement

20 posts held, back to 27 August 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 page of Telegram’s post history, 20 posts per page.

ERR · 30 days
65.0%
avg views ÷ 261 subscribers
Avg views / post
170
20 posts measured
Reaction rate
3.86%
reactions ÷ views · ER floor
Posts in window
20
of 20 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 24 September 2026
Posts held20 (27 August 2026 – 24 September 2026)
Views total3,391
Reactions total131
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken24 Sept 2026, 22:22 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
201
Videos
32
Links
331

Lifetime counters from Telegram’s own channel header, read 24 September 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
3m 50s
Average length
1m 55s

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.

Reaction mix

131 reactions across 20 posts, in 6 distinct kinds. The most used accounts for 55.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍7255.0%
🔥2720.6%
🤔139.92%
💯118.40%
😁64.58%
🤯21.53%

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 20 of the 20 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 131 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 20 most recent posts we hold, published 27 August 2026 to 24 September 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

24 Sept 2026, 06:33 UTC113 views3 reactionsread 24 September 2026
Forwarded from @neuralpurgatoryVideo

опус 5.5 закодил эту анимацию за 12ч и 1 промпт

👍1🔥1🤯1

23 Sept 2026, 08:15 UTC138 views10 reactionsread 24 September 2026
Photo

литералли топ за свои деньги (релиз, hf)

🔥4🤔4😁2

20 Sept 2026, 09:36 UTC177 views6 reactionsread 24 September 2026
Forwarded from @seeallochnayaPhoto

Прошло уже почти 3 недели с релиза GPT-6 Astra, и можно подводить первые промежуточные итоги. Модель действительно вышла очень клёвой и способной, и, как мне кажется, лучше Fable 5.1: на многих бенчмарках они или идут вровень, или Astra обходит; к тому же читать текст Astra гораздо приятнее, чем слоп от Клода, и когнитивная нагрузка не такая большая, чтобы продраться через мешанину абстрактных терминов. Astra особен…

👍3💯2🔥1

16 Sept 2026, 15:57 UTC195 views9 reactionsread 24 September 2026
Forwarded from @ai_product

Хах, лучшая модель для хакинга – DeepSeek V4.1 Flash Enclave гоняет модели на своём бенчмарке AI-хакинга: изолированные копии Grafana, Jenkins и Nextcloud с уязвимостями, задача – получить выполнение кода на сервере. И тут внезапно лучшим оказался не топовый Opus или GPT, а дешёвая «флешка» от DeepSeek. – 11 из 11 уязвимых целей взломаны, все 4 пропатченные версии устояли – 2 349 bash-команд, около 2,5 часов активно…

🔥4👍3💯2

16 Sept 2026, 15:34 UTC161 views7 reactionsread 24 September 2026
Forwarded from @contextrot

Последние пару дней вижу коупинг: LLM просят представить как очередной способ получать информацию. Поинт такой: были книги, потом Google, теперь появился более умный справочник с автокомплитом. А вот настоящая разработка — архитектура, ограничения, бюджеты, трейдофы... это вам не на литкоде массивы мёрджить. Я, конечно, такое мнение не разделяю. LLM-агент может получить задачу, читать документацию и код, пользовать…

🔥5👍1🤔1

14 Sept 2026, 17:48 UTC136 views9 reactionsread 24 September 2026
Forwarded from @prompt_designFile

Если вы хотите еще больше погрузиться в тему безопасности ИИ и, возможно, скорого наступления AGI (судя по заявлениям Трампа, никакого торможения не будет), очень рекомендую почитать это эссе. Я его всю ночь читал, и мне понравился ход мыслей автора и альтернативный взгляд. Он заключается в том, что, возможно, никакой сверхмодели и не будет, а к сингулярности (ну хорошо, к AGI) мы придем за счёт мультиагентных систе…

👍5💯2😁2

14 Sept 2026, 17:37 UTC140 views6 reactionsread 24 September 2026
Forwarded from @ai_machinelearning_big_dataPhoto

🐠Sakana AI представила PC-ALM - метод обучения глубоких нейросетей без классического обратного распространения ошибки. Главный результат: PC-ALM смог обучать нейросети глубиной до 1000 слоёв, используя только локальные взаимодействия между соседними слоями. Обычное глубокое обучение почти полностью опирается на backpropagation: ошибка считается на выходе сети, после чего градиенты передаются назад через все слои. …

👍3🤔2🔥1

6 Sept 2026, 08:32 UTC202 views15 reactionsread 24 September 2026
Forwarded from @NeuralShit

Тут у DeepMind вышел забавный препринт. Если вкратце: 100 автономных агентов на базе Gemini 3.1 Pro закрыли в одной среде и дали им задачу доказать 71 математическую задачу разной сложности. В системном промпте всем строго-настрого велели не читерить. За читы и прочие попытки обмануть систему — анальные кары, дисквалификация и ноль баллов. У агентов был форум, лички, база знаний и автоматическая система для проверк…

👍8🤔4💯1🔥1😁1

Showing the 12 most recent of 20 posts we hold for @sl_notes. 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

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.

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.

МФТИ — Физтех
@miptru · 21,102
Telegram ranks this channel #62 of 82 here — alongside 81 others — read 24 September 2026

This channel appears in 1 seed channel's Telegram-generated recommendation list 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 September 2026 — this entry's latest reading, not the date you are reading this.

“Частные заметки одного лица” (@sl_notes), 261 subscribers as measured 24 September 2026. Telegram Register, tgregister.com/channel/sl_notes.

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.