Crypto & trading — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 10 August 2026 and assigned it the closest of 31 fixed categories, at 92% 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 why it has no browse page of its own yet.
Observations
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
Content that also appears on other registered channels
Posts published here appear word for word on 1 other registered channel. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.
Matching posts — open both and compare (1 of the pairs behind the counts below)
Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.
What this cannot establish
MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.
Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. None of the 1 matches recorded here fall after that date, so for this entry we cannot say whether any of them carried a credit. The duplication is measured; the absence of attribution is not.
“Published first” means first in this corpus. We hold 30 comparable posts for this entry, running 4 August 2026 to 7 August 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.
The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.
Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).
Across the whole group of 2, the earliest publisher we hold is @triple_stock. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_mutual, last confirmed 8 August 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
Also posting the same content
This channel’s posts match, word for word or near enough, posts on 1 other registered channel, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.
Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
8 measurements spanning 7 days, net +238. 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 21,488–21,798 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
13 Aug 2026, 00:34
21,762
+64
11 Aug 2026, 23:53
21,698
+29
10 Aug 2026, 23:02
21,669
+39
9 Aug 2026, 19:58
21,630
+9
8 Aug 2026, 21:40
21,621
+56
7 Aug 2026, 21:51
21,565
+10
7 Aug 2026, 01:25
21,555
+31
6 Aug 2026, 02:31
21,524
first reading
Engagement
63 posts held, back to 4 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 17 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
44.0%
avg views ÷ 21,762 subscribers
Avg views / post
9,570
63 posts measured
Reaction rate
0.752%
reactions ÷ views · ER floor
Posts in window
63
of 63 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
Window
Rolling 30 days · latest post in window 12 August 2026
Posts held
63 (4 August 2026 – 12 August 2026)
Views total
602,740
Reactions total
4,535
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
12 Aug 2026, 23:08 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
3,825 reactions across 51 posts, in 17 distinct kinds. The most used accounts for 41.0% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
1,570
41.0%
👍
623
16.3%
🤮
394
10.3%
🔥
247
6.46%
🙏
241
6.30%
🤬
159
4.16%
🤔
120
3.14%
😱
112
2.93%
😁
111
2.90%
👏
102
2.67%
🤯
86
2.25%
👀
14
0.366%
🎉
11
0.288%
👻
11
0.288%
😨
10
0.261%
😢
9
0.235%
🤩
5
0.131%
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 63 of the 63 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 4,535reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 63 most recent posts we hold, published 4 August 2026 to 12 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.
#테마섹 #삼성전자 #SK하이닉스 #한국
12일 관계부처 등에 따르면 싱가포르 테마섹은 최근 삼성전자 와 SK하이닉스 에 대한 투자를 결정하고 투자 집행 시점을 타진하기 위해 한국 정부와 접촉한 것으로 확인됐다.
투자 방식은 외부 자산운용사를 통한 위탁운용이 아닌 내부 인력을 통한 직접 투자 방식을 택한 것으로 전해졌다. 금융당국 한 관계자는 "삼성전자와 SK하이닉스 주가가 최근 정부의 단일종목 레버리지 상장지수펀드(ETF) 허용 이후 극심한 변동성을 보이는 국면에서 자금 집행 시점 등을 타진하기 위해 접촉한 것으로 알고 있다"고 전했다. 테마섹이 한국 증시에 투자하는 것은 이번이 처음이다.
https://view.asiae.co.kr/article/2026081210232989087
* 매우 중요한 내용이 많이 나온 Cantor의 FMS 리뷰
- "비트 수요가 공급을 5~10%포인트 상회하며 이 격차가 이번 10년 내내 지속될 것"이라는 언급
- 컨센서스는 향후 2개 분기 내 메모리 가격 정점을 예상하고 있지만, 업계 관계자들과의 펀더멘털 논의는 전혀 다른 이야기를 전하고 있음
- (루빈울트라의 HBM) 디스펙과 관련해서는 투자자들이 원인을 잘못 해석하고 있음. 이는 전적으로 공급 가용성의 문제이지 수요 파괴가 아님
- HBM4 가격계약 : SK하이닉스가 엔비디아에 GB당 32달러, 브로드컴에 36달러, AMD에 40달러로 계약을 확정한 것으로 파악
- 트렌드포스는 낸드에 대해 27년 하반기부터 가격하락을 예상했는데, 그러나 Cantor의 대화는 상당히 긍정적이었고 부정적 데이터 포인트는 어디에서도 찾을 수 …
Cantor) FMS(Future of Memory and Storage) 2026 후기: ASP 정점 논쟁 vs 수요 지속성, 주가는 이미 저점권
■ 총평
FMS(Future of Memory and Storage) 2026 컨퍼런스는 올해도 성황이었으며, AI 주도 메모리 슈퍼사이클이 진행되는 가운데 NAND, DRAM, HBM, HBF 전반의 개발 동향에 대한 관심이 뜨거웠습니다. 새로운 아키텍처와 애플리케이션, 워크로드가 메모리 업체들의 공급 능력을 크게 웃도는 수요를 창출하고 있다는 점이 분명해졌으며, 일부 대화에서는 비트 수요가 공급을 5~10%포인트 상회하고 있고 이 격차가 이번 10년 내내 지속될 것이라는 언급이 나왔습니다.
최근 메모리 주식이 조정을 받으며 바이사이드 컨센서스가 향후 2개 분기 내 메모리 가격 정점을 예상하…
시타델 증권에 따르면, 대규모 포지션 축소 이후 시스템매매 투자자들이 다시 주식 비중을 늘릴 준비를 하고 있다.
“레버리지 리셋은 대부분 마무리됐고, 변동성이 낮아지면서 시스템 전략들이 다시 익스포저를 확대할 수 있는 여지가 생겼다. 시장 상승 종목의 폭(Breadth)도 개선되고 있고, 종목 간 상관관계는 사상 최저 수준에 가까우며, 투자자들은 점점 더 상승 가능성에 돈을 지불하려는 모습을 보이고 있다.”
시타델은 시장 반등 가능성을 뒷받침하는 여건이 점차 형성되고 있다고 평가했다.
러브너는 고객에게 보낸 보고서에서
“다음번 의미 있는 기계적 자금 흐름은 디레버리징이 아니라 리레버리징이 될 가능성이 있다.”
고 썼다.
** (특히 메모리 반도체의) 레버리지 물량이 모두 털렸고 다시 익스포져 확대 움직임이 관찰되며 이는 시스템 매수…
2Q26 CoreWeave Conference Call 중
고객과 최종 사용자가 사업을 영위하는 지역에서 직접 서비스를 제공함에 따라, 해외 시장이 주요 성장 동력으로 자리 잡을 것으로 예상합니다. 종합적으로 볼 때, 2030년까지 최소 8GW의 전력 용량을 확보하겠다는 목표에 대한 가시성이 매우 높습니다.
앞으로 수년간 수요가 공급을 상당히 초과할 것으로 예상합니다. 이러한 환경에서는 단순히 전력에 접근할 수 있다는 것만으로는 충분하지 않습니다.
2분기 말 수주잔고는 1,040억 달러로 전년 동기 대비 46% 증가했습니다. 여기에는 3분기 초 새롭게 확보한 250억 달러 이상의 순신규 고객 계약은 포함되지 않았습니다.
기존 수주잔고 가운데 50% 이상은 이미 고객에 대한 서비스 제공이 시작된 계약과 연계돼 있습니다. 올해 말까지는 서…
IBM, Together AI와 2.4억 달러 규모 AI 인프라 계약 체결
: IBM과 Together AI는 2.4억 달러 규모 다년 계약 체결. IBM Cloud에 NVIDIA HGX B300 기반 대규모 AI 추론 클러스터를 구축하며 2027년 1분기 가동 예정
: Together AI는 해당 클러스터를 활용해 오픈소스 AI 모델 추론 서비스 제공. IBM Cloud에서 HGX B300과 Spectrum-X 이더넷을 활용한 최초의 전용 대규모 추론 클러스터
: NVIDIA에 따르면 HGX B300 기반 시스템은 이전 세대 대비 AI 팩토리 처리량을 최대 30배 개선하도록 설계
: Together AI는 최근 83억 달러 밸류에이션으로 8억 달러 규모 시리즈 C 투자 유치. 추론, 학습, 파인튜닝, 에이전틱 워크플로우를 제공하며 현…
* 진 먼스터(Deepwater mgmt)
- 엔비디아와 금융사들의 $500B 플랫폼 파트너쉽에 대해
"이 대형 호재에도 불구하고 엔비디아 주가와 시장 반응은 상당히 미지근했습니다(muted reaction)."
“투자자들은 AI 빌드아웃이 얼마나 초기 단계인지 제대로 인식하지 못하고 있습니다.”
https://www.cnbc.com/video/2026/08/10/deepwaters-gene-munster-tech-investors-not-appreciating-how-early-we-are-into-ai-buildout.html
1. 미 SEC가 데이터센터 ABS 발행 시 2008년 금융위기 방어책인 '위험보유' 규제 예외를 인정하며 AI 인프라 자금 조달의 빗장을 완전히 해제함.
2. 데이터센터를 단순 금융 자산이 아닌 실물 자산군으로 분류하여, 발행사의 부채 의무 보유 부담을 없애고 자본 효율성을 극대화함.
3. 금융 시스템 안정보다 AI 산업 경쟁력 강화를 우선시하는 미 규제 당국의 강력한 'AI 하이퍼 사이클' 지원 의지.
👍58❤13🤔2🔥1
Showing the 12 most recent of 63 posts we hold for @cahier_de_market. 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 — 31,475 of 1,151,006entries 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 7 registered channels — 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.
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.
“카이에 de market” (@cahier_de_market), 21,762 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/cahier_de_market.
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.
