Other / unclassifiable — 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 12 September 2026 and assigned it the closest of 31 fixed categories, at 83% 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
27 measurements spanning 93 days, net -137. 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 5,738–5,917 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 27
Measured (UTC)
Subscribers
Change
7 Nov 2026, 06:49
5,759
-8
3 Nov 2026, 21:55
5,767
-5
31 Oct 2026, 23:54
5,772
-2
29 Oct 2026, 09:09
5,774
-3
26 Oct 2026, 16:10
5,777
-7
23 Oct 2026, 18:48
5,784
-9
21 Oct 2026, 02:36
5,793
-1
17 Oct 2026, 20:47
5,794
-1
15 Oct 2026, 05:17
5,795
-8
12 Oct 2026, 00:40
5,803
-12
5 Oct 2026, 10:01
5,815
-7
27 Sept 2026, 13:57
5,822
-14
18 Sept 2026, 15:58
5,836
+2
14 Sept 2026, 10:37
5,834
-2
10 Sept 2026, 11:55
5,836
+4
5 Sept 2026, 13:01
5,832
-4
1 Sept 2026, 15:42
5,836
+4
30 Aug 2026, 00:53
5,832
-6
27 Aug 2026, 01:35
5,838
-7
23 Aug 2026, 21:35
5,845
first reading
Engagement
40 posts held, back to 1 June 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 10 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
26.9%
avg views ÷ 5,759 subscribers
Avg views / post
1,550
7 posts measured
Reaction rate
0.081%
reactions ÷ views · ER floor
Posts in window
7
of 40 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 3 of 7 measured posts that carry a reaction reading, and over those same posts' views.
What these figures were computed from
Window
Rolling 30 days · latest post in window 4 November 2026
Posts held
40 (1 June 2026 – 4 November 2026)
Views total
10,857
Reactions total
6
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
4 Nov 2026, 19:05 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
Video runtime
1m 08s
Average length
1m 08s
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
61 reactions across 16 posts, in 4 distinct kinds. The most used accounts for 77.0% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🫡
47
77.0%
🤯
8
13.1%
🙊
3
4.92%
🤮
3
4.92%
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 40 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 61 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 40 most recent posts we hold, published 1 June 2026 to 4 November 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
Telegram’s own ‘edited’ marker: 0 of 7 posts held from the last 30 days (0%) 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).
#투자
최근 한발짝 멀리서 지켜본 시장과 주변 시장참여자들의 얘기를 들어보면, 현재는 '공부할 수록 더 깨지는 장' 이 가장 정확하지 않을까 싶다. AI를 피해 도피해도 깨지고, 다른 섹터 수급상황이 좋아보여 옮겨도 결국엔 깨지는 장. 원래 하락장엔 가만히 있는게 답이 아닐까 싶다.
투자자는, 더 좁게 들어가 '주식' 투자자는 아무리 매크로를 보고 거시적인 관점을 갖는다 해도 현실감각이 떨어진다. 주식은 기업과 경제를 대변하지 산업을 대변하진 못한다.
지금은 부푼 '꿈'을 가지고 한번쯤 움직여 볼때다.
https://blog.naver.com/invesqueeze/224464897023
삼성전자·SK하이닉스, 주주환원 210조 원+α 기사 정리
① SK하이닉스: 총 100조 원
- 기존 자사주 매입·소각 40조 원
- 추가 자사주 매입 30조 원
- 현금배당 30조 원
- 별도로 임직원 성과급 지급용 자사주 10조 원 매입 추진
② 삼성전자: 총 110조 원
- 현금배당 30조 원
- 추가 주주환원 80조 원(자사주 매입·소각 중심 예상)
- 향후 FCF의 50% 이상을 주주환원하는 정책으로 확대할 가능성
https://www.hankyung.com/article/2026102787811
#ai
최근 앤트로픽의 매출 성장에 둔화에 대한 얘기가 많다. 비ai유저 혹은 단순 숫자놀음에 동기화 된 금융권에겐 당연히 크리티컬하게 받아들일 수 밖에 없기도 하다.
하지만 ai유저들에겐 일찍이 트렌드는 두어달 전부터 gpt로 옴겨졌으며, 최근엔 muse를 통해 또한번 트렌드가 실시간으로 대중들에게 이동하고 있다.
최근 일론의 인터뷰를 보면 코딩에 특화된 클로드가 그록보다 현재 앞선건 사실이지만, 향후 3년안에 그록이 따라잡는다고 확언한다. 제품을 직접 만드는 공학적인 측면을 우위로.
ai사이클은 단순 끝나고 지속되고의 문제가 아니라, 사람마다 어느정도 인지하고 알고 있느냐의 차이가 아닐까 싶다.
https://youtube.com/shorts/jyQ3R1sRKIM?si=EXM-yHmskylRLhmq
#ai #반도체
응..?
실제로 제미나이 4 아르곤은 코딩 능력을 측정하는 '딥SWE v1.1'과 '바이브코드 벤치' 등 성능지표에서 경쟁사인 오픈AI와 앤트로픽 모델을 능가하는 점수를 받았다.
금융·법률 업무 능력을 평가하는 성능지표에서도 경쟁 모델을 능가하거나 압도했고, 사이버보안 능력을 재는 'CWE-벤치 v1' 등에서는 GPT-6 아스트라와 공동 1위 수준을 기록했다.
구글은 이처럼 복잡한 문제를 해결하는 특장점을 살릴 수 있도록 출력 토큰 제한을 기존 6만4천 토큰에서 업계 최고 수준인 100만 토큰으로 확장했다.
https://magazine.hankyung.com/business/article/202610016415b
#투자
얼마전 '실리콘밸리의 1% 버블과 99% 맹점' 에 대한 글에서, 대 ai시대임에도 매우 아이러니하게 실리콘밸리가 아닌 현실의 대중들에겐 현재를 살아가는 생계와 연관된 것이 가장 중요하고 변하지 않는다고 글을 썼다.
중요한건 작금의 '생계'와 연관된 우리의 일자리 구조가 결국 ai를 통해 파괴적으로 변할 것이며, 그 일자리의 소싱과 편의성 또한 앞으로 ai의 도움을 받을 것이란 것이다.
https://blog.naver.com/invesqueeze/224427160246
#ai #플랫폼
실리콘밸리 밖의 평범한 사람들이 매달 고민하는 건 "어떤 새로운 AI 툴을 써볼까?"가 아니다.
이들에게 진짜 필요한 기술은 화려한 생성형 AI 챗봇이 아니라, "내 생활비를 실질적으로 깎아주고, 당장의 현금 흐름을 숨통 트이게 해주는 기술"인 것이다.
상위 1%의 편리함을 만드는 기술보다, 99%의 먹고사는 문제를 해결하는 기술이 훨씬 더 거대하다.
https://blog.naver.com/invesqueeze/224424823747
이거 약간 유튜브 프리미엄 구독할때 국가 인도로 지정하면 싸게 구독할수 있는 그런건가
클로드 싸게 쓰고 싶으면 키미 문샷 구독ㄱㄱ
https://t.me/invesqz/3477
Showing the 12 most recent of 40 posts we hold for @invesqz. 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
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
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.
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.
조기주식회 공부방 @EarlyStock1 · 24,391 Telegram ranks this channel #64 of 91 here — alongside 90 others — read 16 September 2026
YM리서치 @ym_research · 39,856 Telegram ranks this channel #89 of 89 here — alongside 88 others — read 2 September 2026
This channel appears in 2 seed channels' Telegram-generated recommendation lists 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 7 November 2026 — this
entry's latest reading, not the date you are reading this.
“[인베스퀴즈]” (@invesqz), 5,759 subscribers as measured 7 November 2026. Telegram Register, tgregister.com/channel/invesqz.
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.