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Telegram profile photo for Surf 🏄‍♂️

Channel

Surf 🏄‍♂️

@jjsurf

On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry

54subscribers

+2 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-1003975854327
TypeChannel
Username@jjsurf
CreatedBetween 1 April 2026 and 26 July 2026— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded10 August 2026
Last confirmed live15 August 2026
Measurements held4
Confirmed unchanged1 time, most recently 15 August 2026
On Telegramt.me/jjsurf

Growth

5254537 August 2026 — 52 subscribers7 August 2026 — 53 subscribers10 August 2026 — 53 subscribers15 August 2026 — 54 subscribers7 August 202615 August 2026
4 measurements spanning 8 days, net +2. 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 52–54 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
15 Aug 2026, 00:5654+1
10 Aug 2026, 09:3053no change
7 Aug 2026, 14:3853+1
7 Aug 2026, 07:3352first reading

Engagement

11 posts held, back to 26 July 2026the 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
81.1%
avg views ÷ 54 subscribers
Avg views / post
43.8
11 posts measured
Reaction rate
11.0%
reactions ÷ views · ER floor
Posts in window
11
of 11 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 8 August 2026
Posts held11 (26 July 20268 August 2026)
Views total482
Reactions total53
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken10 Aug 2026, 09:30 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.

Reaction mix

53 reactions across 11 posts, in 8 distinct kinds. The most used accounts for 47.2% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
2547.2%
🔥1222.6%
👍917.0%
35.66%
🗿11.89%
😱11.89%
🤔11.89%
🤯11.89%

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 11 of the 11 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 53reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 11 most recent posts we hold, published 26 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

2 Aug 2026, 08:06 UTC36 views1 reactionsread 10 August 2026
File

💢 Продолжаю делиться методами оптимизации ИИ инференса из моего RnD предыдущие слои Layer-1. Infrastructure Layer-2.Agent Internet Layer Ниже Layer-3. Protocol Layer - A2A (Agent-to-Agent Protocol) - MCP (Model Context Protocol) - ACP (Agent Capability Protocol) - ANP (Agent Negotiation Protocol) - AGORA - AGP (Agent Gateway Protocol) - TAP (Tool Abstraction Protocol) - OAP (Open Agent Protocol) - FCP (Function Ca

1

2 Aug 2026, 07:48 UTC36 views3 reactionsread 10 August 2026
File

💢 Продолжаю делиться методами оптимизации ИИ инференса из моего RnD первый слой тут Layer-1. Infrastructure 2й слой - Agent Internet Layer - Autonomous Agents - Multi-Agent Systems - Communication Protocols - Agent Memory (Short/Long-Term) - Embedding Stores (Pinecone, Weaviate) - Agent Mesh Networks - Agent Identity State - Execution Environments - Tool Use Modules Для Layer 2 тоже есть быстрые и долгие выгоды

2🔥1

31 Jul 2026, 21:09 UTC40 views8 reactionsread 10 August 2026

🎙️ Мэттью Макконахи клевый чел 1 Он не стесняется быть иным и написал глубокую для себя 📗 книгу на основе дневников, которые вёл 35+ лет (!!!) 2 Он публично делится своей историей про «кризисе комфорта» и потерю смысла в молодости, раскатывая идеологию на всех мужчин: Мэттью утверждает, что не трудности, а избыток комфорта - главная угроза («краткосрочный друг, но долгосрочный враг») Избыток выбора превращает лю

52🗿1

29 Jul 2026, 11:33 UTC52 views9 reactionsread 10 August 2026

🧹 ИИ гигена У меня в связке с Claude завёлся ритуал, который зря недооценивают - ежемесячная гигиена. Памяти, промптов, инструкций, файлов и тд Проблемы 2: модели очень быстро меняются (в том числе методологически) и наследие - когда ты долго работаешь с ассистентом, у него накапливается несколько слоёв контекста - инструкция, память, лог решений, база знаний и тп Все это становится неэффективным и они расходятся

5🔥3👍1

27 Jul 2026, 20:13 UTC49 views1 reactionsread 10 August 2026

🎙️ Попались вопросы, которые OpenAI, Anthropic, Google, Nvidia, Meta спрашивают на технических собеседований на позицию AI PM. Во фронтирах собес на AI PM - это не «знаешь ли ты промпты», а можешь ли объяснить механику под капотом, обосновать выбор модели и задизайнить систему на трейд-оффах и отказах. Валят обычно на глубине - transformers, attention, режимы отказа RAG. Специфично к каждой компании: • OpenAI: что

😱1

26 Jul 2026, 12:25 UTC57 views5 reactionsread 10 August 2026
Photo

🆕🤖️ Anthropic выкатили два гайда про то, как теперь работать с моделями 5-го поколения. 🔗 [Context Engineering] · [Field Guide to Fable] Суть обоих в одном: старый подход «обвешать модель правилами» больше не работает. Изменения: Разгружай, а не диктуй (context engineering): • Снимай лишние ограничения - гайдрейлы для старых моделей теперь мешают. Anthropic вырезали 80% системного промпта Claude Code без потери

👍3🔥1🤯1

26 Jul 2026, 07:41 UTC47 views3 reactionsread 10 August 2026
Photo

🇨🇳 Хорошее видео, которое отлично объясняет, почему Китай в ИИ моделях обходит фронтиры во многих вопросах внутри гонки LLMs Если кратко, то реальная битва сейчас не на «фронтире» (кто сделает самую мощную закрытую модель), а на открытых весах - и там уже лидируют китайцы. Когда закрытый фронтир становится слишком дорогим или слишком «залоченным», рядом лежит открытая китайская альтернатива которая часто лучше по

👍1🔥1🤔1

Showing the 11 most recent of 11 posts we hold for @jjsurf. 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.

Citation-graph rank

Citation-graph rank — 443,948 of 1,548,671entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

Forward network

Republished by

Channels on the register that have forwarded this channel's posts into their own feed.

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.

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 15 August 2026 — this entry's latest reading, not the date you are reading this.

“Surf 🏄‍♂️” (@jjsurf), 54 subscribers as measured 15 August 2026. Telegram Register, tgregister.com/channel/jjsurf.

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.