Other / unclassifiable — 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 44% 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.
Views per post sit far above this size band
22,400 average views per post against 18,438 subscribers — an engagement rate of 121.4%. Across the 55,140 registered channels in the same cohort — 10,000–31,619 subscribers — the middle half sit between 4.19% and 20.1%, with a median of 9.77%.
What this was computed from
Window
30 days (13 July 2026 – 12 August 2026)
Posts measured
29 of 29 published in the window (0 exact, 29 rounded by Telegram)
Views totalled
649,120
Mature posts only
124.6% over 27 posts read at least 24h after publication
When this is recorded. A channel is listed here only when its engagement rate sits at or above the 99th percentile of its cohort and is at least 3× away from that cohort’s median — above it — on both the all-readings figure and the mature-only figure. The percentile alone would be circular: a percentile cut puts the same share of every cohort in the tail whatever the data looks like. The distance from the median is what makes it a statement about this channel.
This is not a verdict, and the direction is not a quality signal.A low rate has many innocent causes — audiences that read in the Telegram app without opening the channel, a subscriber base built long before the current output, an audience in a different timezone from our reading. A high rate has innocent causes too: a post that travelled far beyond the channel’s own subscribers will do it. We publish the measurement and the distribution it sits in. The full cohort baselines are downloadable, so this comparison can be reproduced rather than trusted.
Recorded under the key err_high, last confirmed 12 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.
Growth
9 measurements spanning 7 days, net +764. 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 17,581–18,575 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
13 Aug 2026, 05:47
18,460
+22
12 Aug 2026, 07:53
18,438
+59
11 Aug 2026, 07:11
18,379
-2
10 Aug 2026, 09:21
18,381
+12
9 Aug 2026, 12:41
18,369
+14
8 Aug 2026, 16:05
18,355
+29
7 Aug 2026, 17:12
18,326
+251
6 Aug 2026, 14:43
18,075
+379
6 Aug 2026, 02:34
17,696
first reading
Engagement
30 posts held, back to 29 July 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 18 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
122.1%
avg views ÷ 18,460 subscribers
Avg views / post
22,500
30 posts measured
Reaction rate
0.719%
reactions ÷ views · ER floor
Posts in window
30
of 30 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
30 (29 July 2026 – 12 August 2026)
Views total
675,960
Reactions total
4,857
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
13 Aug 2026, 14:00 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
≈1,750
Links
≈429
Lifetime counters from Telegram’s own channel header, read 13 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Reaction mix
3,883 reactions across 25 posts, in 13 distinct kinds. The most used accounts for 51.0% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
1,979
51.0%
👍
961
24.7%
😱
295
7.60%
👌
209
5.38%
🤬
95
2.45%
🔥
67
1.73%
😭
61
1.57%
🤔
51
1.31%
💯
49
1.26%
🙏
49
1.26%
👏
32
0.824%
🤯
28
0.721%
✍
7
0.18%
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 30 of the 30 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 4,857reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 30 most recent posts we hold, published 29 July 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.
매크로 관점 tweak: 9월 미국 금리 인상 확률 39.9% (7월 말 66%)
시장 메커니즘은 복잡하지만, 아주 단순화해 보면 현재 글로벌 성장의 주축은 AI 인프라 투자.
투자 자금 조달이 채권 시장으로 확산되면서 회사채 공급 증가 → 채권 가격 하락(고금리 유지) 양상.
만약 향후 국채 금리가 급격히 하락하는 가운데 회사채 크레딧 스프레드가 확대된다면, 이는 단순한 금리 안정이 아닌 글로벌 경기 침체 시그널로 해석할 수 있으며, 모든 위험 자산의 매도 대응이 필요.
That is your sell signal (자세한건 글로 나중에)
https://t.me/kkkontemp/2510
필자가 팔로우하는 Ironside Economics:
클리블랜드 연은과 블룸버그의 근원 CPI 추적 모델은 각각 0.21%와 0.15%를 나타내고 있으며, 블룸버그 집계 경제학자들의 컨센서스 전망치는 0.23%입니다. 7월과 8월에 0.2%대를 기록한다면, PCED(개인소비지출 물가지수) 수정치가 발표되기 직전인 9월 연준 회의 시점의 연율화 물가상승률은 2.27%가 됩니다. 근원 CPI가 컨센서스 전망치를 하회할 수 있음을 시사하는 4가지 요인이 있습니다.
첫째, 관세 환급과 중국의 인볼루션(과잉 생산 경쟁) 진통이 근원 상품의 디스인플레이션(물가상승률 둔화)에 추가적인 압력을 가할 가능성이 높습니다.
둘째, 팬데믹 이후 나타난 음의 계절성과 임금 상승세 둔화가 주거비 제외 서비스 물가에 하방 압력을 가할 것으로 보입니다.
셋째, 주…
내일은 CPI day
일단 가장 잘 맞추는 UBS 코멘트:
근원 소비자물가지수(Core CPI): UBS US Econ 0.24%, 블룸버그 컨센서스 0.26%, UBS Nowcast 0.18%
지난달 발표된 놀라울 정도로 둔화된 수치(-0.02%) 이후, 계절조정 기준 근원 CPI가 0.24% 상승하며 보다 정상적인 속도를 되찾을 것으로 예상합니다. 다만 이는 지난해 7월(+0.31%)보다는 여전히 몇 bp(0.01%p) 낮습니다.
최근 발표한 US Inflation Monthly 보고서에서 언급했듯이, 저희는 6월의 둔화세에 의미를 크게 두지 않으며, 6월의 둔화가 연장되기보다는 7월 및/또는 8월 CPI의 강한 상승으로 이어질 위험이 더 크다고 보고 있습니다.
저희의 근원 CPI 전망치는 현재 블룸버그 컨센서스 평균 예상치보다 …
예를 들어, Citi
메모리 - 우리는 왜 시장과 반대(Contrarian) 입장을 취하는가?
약세(Bearish)를 보이는 HBM 체크 결과(스펙 하향 조정, 하이닉스의 2027년 HBM4 ASP가 예상보다 낮음)와 SNDK(샌디스크)의 바이사이드 예상치(Bogey) 미달, 그리고 2027년 NAND 전망에 대한 부정적 기류로 인해 메모리 주가가 다시 한번 조정을 받았습니다. 그러나 당사의 업계 체크에 따르면 HBM 숏티지(공급 부족)는 2027~2028년에 더욱 심화될 것이며, DRAM/NAND의 공급 충족률(Fulfillment rate)은 2027년에 훨씬 더 낮아질 것으로 예상됩니다. 당사가 파악한 구체적 내용은 다음과 같습니다.
a/ HBM 스펙 하향(사실이라 하더라도): 이는 수요 문제가 아니며, 공급은 2028년까지도 훨씬…
최근 SemiAnalysis의 보고서나 분석글이 시장에 영향을 미치는 경우가 종종 있으나, 참고할때 주의가 필요해 보임
자극적 보고서 작성 경력: 6개월전에 Micron의 HBM4 점유율을 Zero라고 주장했다가 사실무근으로 드러나 논란이 되었고, 대만 기업 디스나 CPO 관련 이슈 등 자극적인 주장을 던진 후 시장이 흔들리면 나 몰라라 하는 식의 패턴이 반복되고 있음
노이즈 및 시장 변동성 유발: 자극적인 팩트 미확인 주장으로 시총을 크게 흔들어 놓은 뒤 시간이 지나 회복되는 양상이 자주 발생
바이사이드 (기관 투자자) 수용도 주의: 일부 바이사이드에서 이를 맹신하는 경향이 있으나, 기본 팩트체크 없이 노이즈성 주장에 휩쓸려 스탠스를 정하는 것은 위험할 수 있음
SemiAnalysis 측 자료는 신뢰도 높은 검증 체계를 거쳤다기보다…
지원 사격:
Citi:
우리가 보기에 현재 AI가 견인하는 메모리 상승 사이클(Upcycle)은 아직 초입 단계에 있으며, AI 수요가 DRAM과 NAND 모두를 견인함에 따라 2001년~2007년의 NAND 상승 사이클 성과를 상회할 가능성이 있습니다. 지속적인 HBM 공급 부족은 반도체 제조사들이 스케일아웃(Scale-out)을 추진하도록 만들고 있으며, GPU당 HBM 탑재량 감소에도 불구하고 AI 시스템당 총 HBM 용량은 여전히 433% 급증할 것으로 전망됩니다. 중장기 실적 가시성이 확보된 만큼, SK하이닉스가 3분기 실적 발표 전에 주주환원 프로그램을 공유할 것으로 예상합니다. 매수(Buy) 투자의견을 유지합니다.
MS (Morgan Stanley):
지금까지 메모리 산업에서 가장 가파르게 진행되었던 조정은 일단 일단락된 것으…
오늘 메모리 반도체 약세 배경
1) 샌디스크 실적 실망
2) 어제부터 Semianalysis + 대만증권사 부정적 센티 영향 코멘트들
1. 엔비디아·CSP의 메모리 스펙 하향 조정 (비용 절감 목적)
HBM 용량 축소: 하이퍼스케일러(CSP)들의 원가 절감 요청에 따라, Rubin Ultra의 주력 메모리가 기존 HBM4E 12-Hi(384GB)에서 HBM4 8-Hi(192GB~256GB)로 하향 조정되었습니다. (288GB/384GB 12-Hi 옵션도 병행 유지)
Vera CPU 용량 감소: SOCAMM 용량이 2026년 하반기 192GB에서 96GB로, 2027년 1분기에는 일부 SKU 기준 64GB까지 축소됩니다.
업계 전반의 흐름: AMD(Meta 향 맞춤형 MI450) 및 구글(자체 TPU) 역시 비용 부담을 줄이기 위해 이…
시티 글로벌 경기 서프라이즈 지수
경기 프록시인 PMI, ISM, 구리등 호조를 보임에도 주식시장에는 최근 드로우다운으로 여전히 공포가 많은듯
👍59😭21❤12👌5🤯4🔥1
Showing the 12 most recent of 30 posts we hold for @kkkontemp. 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 — 16,658 of 1,189,255entries 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 8 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.
“KK Kontemporaries” (@kkkontemp), 18,460 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/kkkontemp.
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.