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Channel

박강찬朴剛燦

@chanbobindustry

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

1,456subscribers

-9 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 1,000–3,162.

Register entry

Telegram ID-1002300552600
TypeChannel
Username@chanbobindustry
CreatedBetween 1 September 2024 and 31 March 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live13 August 2026
Measurements held4
Confirmed unchanged1 time, most recently 13 August 2026
On Telegramt.me/chanbobindustry

Growth

1,4561,4651,460.57 August 2026 — 1,465 subscribers7 August 2026 — 1,465 subscribers10 August 2026 — 1,460 subscribers13 August 2026 — 1,456 subscribers7 August 202613 August 2026
4 measurements spanning 6 days, net -9. 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 1,455–1,466 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
13 Aug 2026, 12:071,456-4
10 Aug 2026, 19:451,460-5
7 Aug 2026, 13:421,465no change
7 Aug 2026, 09:171,465first reading

Engagement

20 posts held, back to 8 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
46.7%
avg views ÷ 1,456 subscribers
Avg views / post
680
7 posts measured
Reaction rate
0.735%
reactions ÷ views · ER floor
Posts in window
7
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 26 July 2026
Posts held20 (8 July 202626 July 2026)
Views total4,759
Reactions total35
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Aug 2026, 09:17 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

72 reactions across 16 posts, in 9 distinct kinds. The most used accounts for 62.5% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
4562.5%
👍1216.7%
🤔68.33%
😭34.17%
🙊22.78%
👏11.39%
🔥11.39%
😁11.39%
🥱11.39%

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 16 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 72reactions 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 8 July 2026 to 26 July 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

26 Jul 2026, 09:34 UTC483 views6 reactionsread 7 August 2026

제가 활동하던 연세대블록체인학회 BAY도 드디어 텔레채널을 개설했네요 많관부 및 많은피드백환영 https://t.me/blockchain_at_yonsei

6

24 Jul 2026, 04:39 UTC604 views4 reactionsread 7 August 2026
Photo

사랑해 난 너밖에 없어 클로드야 정말 진심으로 사랑해 가지마

3🤔1

22 Jul 2026, 04:46 UTC693 views6 reactionsread 7 August 2026

자코비안 추측 반례가 생각보다 논란이 안되네 https://x.com/__alpoge__/status/2079028340955197566 anthropic 수학자가 fable 5 를 사용해서 80년간 안나오던 자코비안 추측의 3차원 반례를 찾았는데, 나는 이게 수학이란 학문의 커리큘럼이나 학습방법론에 엄청 의미가 크다고 생각함 수학은 어느정도 아름다움을 추구하는 학문인데, 이걸 가속해서 벗길 수 있다는 사실부터가 야릇하고, 적당한 수준의 ansatz가 있다면, 실험 사이클을 극도로 가속시킬 수 있다는 걸 실제로 보여줬기 때문에 수학을 배우는 사람의 이데아가 완전히 달라져야 한다고 생각함 본인의 실험실을 상상하고 설계하는 능력을 가지고 토큰(돈)만 충분하다면,,, **추신) 자코비안 추측은 음 부분적으로 완벽하면 전체도 완벽할까?

6

21 Jul 2026, 16:05 UTC814 views8 reactionsread 7 August 2026

요새 새로 나오는 모델들 보면 드는 생각은.. 세트메뉴 구성을 강화한다는 느낌.. 제미나이3.6플래시는 그냥 단일메뉴가 아니라 롯데리아의 케찹이나 초밥집의 와사비나 초생강 같은거임.. 케찹이나 와사비 쭉 짜먹으면서 맛없네 할게 아니라 그냥 세트 안에서 본인의 역할이 있는..

👍5🤔2🥱1

21 Jul 2026, 15:33 UTC611 views1 reactionsread 7 August 2026

제 부동의 원픽은 4년간 하니였는데요, 2026시즌 민지는 정말 엄청난 기대가 되네요 https://youtu.be/NNbaTJX_9go?si=9u3YMVP5HZhhK4fU https://www.youtube.com/watch?v=9MaO43ekbHs

1

18 Jul 2026, 03:27 UTC772 views5 reactionsread 7 August 2026
Photo

매일 눈을 비비게 하는 Codex.... 무한 초기화 무한 감사합니다.. 사실 오늘은 kimi 3 + grok4.5 로 무한가성비 놀이 해보려했는데 저녁으로 미뤄야겠네요

5

17 Jul 2026, 10:57 UTC782 views5 reactionsread 7 August 2026

바이브코딩 하는 사람들의 디렉토리나 지식구조를 까보면 더러운 경우가 많다 내것도 그렇고(주제를 크게 벗어나 있는 일들이 많거나 방법론의 충돌이 많다) 특히 단일 모델만을 사용하는 사람의 경우에 더 그렇고, 오케스트레이션을 통한 사람의 경우에는 그런 경향이 조금 덜하다(교차 검증을 하기 때문에) 어쨌든 llm은 기본적으로 발산하는 성질이 있기 때문에 본인이 생성한 것들에 대한 자아 비판과 회귀를 하는 경향보다는 자기강화를 하고 무한 재생성을 하려는 경향이 강하다 그러므로 아직 agi에 도달하지 못한 우리는 수렴하는 성질의 스코프를 정해주든, 에이전트를 넣어주든, 인간이 calibration 해줘야함 태스크, 하네싱에 따라 Entropy, 프랙탈 지수는 다르기 때문에 토큰 경제성을 위해 어느정도 수준의 비판과 교정을 넣어줄 지는 다르지만

5

14 Jul 2026, 12:52 UTC806 views8 reactionsread 7 August 2026

모델은 많은 사람이 쓰면 멍청해짐 새로운 모델이 나온다거나, 정말 사람이 많이 와서 추론 수요를 할당된 데이터센터가 받쳐주지 않으면 아주 멍청해짐 이번 지피티는 굉장히 아쉬운게, 모델 하네싱을 최적 수준의 지능을 기준으로 맞춰놓은 건지, 조금 멍청해졌더니 핸들을 놓치고 제구력을 잃어서 자꾸 일을 벌리고 그 벌린 일을 고치고 그 규약을 만들고 하다가 아예 다른 방향으로 발산해버리는 것 같음 지피티의 플랫폼이 클로드같아졌다고 했는데, 아직 경험이 부족한지 아쉽긴 함 첫날 새벽에 쓰던 그 맛과는 다름 결국 메모리가 필요한 일이라고 생각하고, 또 그록이 지금 굉장히 좋다고 얘기하고 싶음 아무도 안써서 아우토반이여

5👍1👏1😁1

12 Jul 2026, 12:46 UTC770 views6 reactionsread 7 August 2026
Photo

BASED AI에 대해 들어보셨는가? 정말로 후원문의가 와서 정말로 후원을 해주신단다 예시만 봐도 코인주식력이 올라가지 않는가? (비트,하닉,스엑) 투자 정보/리포트 에 집중된 AI wrapper으로 보인다 당연히 모든 모델이 다 들어가있다 가성비부터 프론티어까지 사용후기도 곧 올려보겠습니다 크레딧$2후원링크

🤔3🙊21

12 Jul 2026, 12:37 UTC674 views1 reactionsread 7 August 2026

그나저나 코덱스 행사 가서 듣다보니 UIUX는 cli보다 코덱스 앱에 대한 비중이 큰 뉘앙스를 받았다(전부 코덱스앱만 시연하도라) 몇달전에 코덱스앱 쓸때는 답답해 죽을뻔했는데 행사 다녀와서 써보니 꽤 나름 쓸만하다 클로드가 개발자를 위한 agi 에 집중한다면 지피티가 사무직을 위한 agi에 더 집중한다는 느낌을 받았다 별개로 주말에 원격 기능을 많이 써보니 클로드는 성능이 그나마 비슷하게 나오고, 지피티는 성능이 많이 모자라진다(실수를 많이함) 오늘 카카오쫀득지피티사용권이 끝나는 날이다 비참하다

1

9 Jul 2026, 19:37 UTC773 views2 reactionsread 7 August 2026
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5시간한도 다썼는데 한시간째 돌아가는중 물론 주간한도 녹아내리는중

2

9 Jul 2026, 19:22 UTC≈5,970 views8 reactionsread 7 August 2026

[gpt-5.6-sol 후기] 1. 직관적 느낌은 일단 체감되게 확 좋다 당연히 fable보다 좋다 2. 자존심 굽히고 클로드의 플랫폼을 따라한 점이 사용성이 더 좋고 마음에 든다 ultra 좋아요 3. 모델이 하나였다가 3개가 됐다 보니 모델 config를 잘 설정해야겠다는 생각이 든다 왜냐하면 4. 코덱스는 지금껏 매우 사용한도가 컸기때문에, 최대한 맥싱하는 세팅을 뒀는데, ultra + fast로 쓰니까 fable보다도 빨리 닳는다 terra와 luna의 플라이휠을 활용.. 앗 5. goal을 사용하지 않아도 여러 턴 + 태스크 설정을 잘 해낸다. 어느정도냐면 사용량 다썼는데 40분넘게 돌아가는중(노래방막곡메타 가능) 6. 최근에 fable을 오케스트레이터로 두고 gpt5.5xhigh를 서브로 호출해서 쓰는 세팅이었다면, 이제

4👍4

Showing the 12 most recent of 20 posts we hold for @chanbobindustry. 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 — 673,423 of 1,350,102entries 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.

Mentions

Named by 1 registered channel — 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.

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

“박강찬朴剛燦” (@chanbobindustry), 1,456 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/chanbobindustry.

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.