NVIDIA, Vera Rubin HBM4 대역폭을 최대 26%까지 조용히 낮추며 NVLink 속도도 감소했습니다. 앞서 NVIDIA의 GTC 2026 발표 이후 보도한 바와 같이, 각 루빈(Rubin) GPU는 원래 288GB의 HBM4 메모리를 탑재해 22TB/s의 대역폭을 제공하며, 3.6TB/s의 NVLink 6 대역폭을 갖춘 것으로 소개되었습니다. 이후 해당 수치는 각각 19.2TB/s와 3TB/s로 하향 조정되었으며, 이는 각각 약 13%와 17% 감소한 수치입니다. 이러한 변경 사항은 72개의 루빈 GPU와 36개의 베라 CPU를 결합한 초대형 베라 루빈 NVL72 구성은 물론, 엔비디아의 소형 HGX 루빈 NVL8 시스템에도 적용됩니다. 가장 큰 감소폭을 보인 부분은 HGX Rubin NVL8의 총 HBM4 대역폭으로, 약…

Channel
Brain and Body Research
@Brain_And_Body_Research
On this record: Topic · Also posting the same content · Growth · Engagement · Reactions · Posts · Citations · Cite this entry
34,752subscribers
-652 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
Register entry
| Telegram ID | -1001656364050 |
|---|---|
| Type | Channel |
| Username | @Brain_And_Body_Research |
| Created | 21 March 2023 — measured — cross-checked against a third-party dataset (ext.tg_channel) |
| First recorded | 6 August 2026 |
| Last confirmed live | 26 October 2026 |
| Measurements held | 48 |
| Confirmed unchanged | 1 time, most recently 26 October 2026 |
| On Telegram | t.me/Brain_And_Body_Research |
Topic
Technology — 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 9 September 2026 and assigned it the closest of 31 fixed categories, at 54% 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.
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.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 26 Oct 2026, 13:20 | 34,752 | -10 |
| 25 Oct 2026, 09:48 | 34,762 | -10 |
| 24 Oct 2026, 07:04 | 34,772 | -3 |
| 23 Oct 2026, 03:57 | 34,775 | -4 |
| 22 Oct 2026, 03:27 | 34,779 | -8 |
| 20 Oct 2026, 20:31 | 34,787 | -7 |
| 19 Oct 2026, 21:46 | 34,794 | -13 |
| 18 Oct 2026, 22:35 | 34,807 | -4 |
| 17 Oct 2026, 20:20 | 34,811 | -1 |
| 16 Oct 2026, 16:45 | 34,812 | +1 |
| 15 Oct 2026, 17:14 | 34,811 | -11 |
| 14 Oct 2026, 15:38 | 34,822 | -15 |
| 13 Oct 2026, 05:16 | 34,837 | -30 |
| 8 Oct 2026, 20:20 | 34,867 | -32 |
| 4 Oct 2026, 11:00 | 34,899 | -75 |
| 25 Sept 2026, 22:59 | 34,974 | -57 |
| 19 Sept 2026, 02:59 | 35,031 | -14 |
| 16 Sept 2026, 18:00 | 35,045 | -22 |
| 14 Sept 2026, 23:20 | 35,067 | -19 |
| 13 Sept 2026, 09:21 | 35,086 | first reading |
Engagement
207 posts held, back to 3 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 145 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 21.4%
- avg views ÷ 34,752 subscribers
- Avg views / post
- 7,440
- 41 posts measured
- Reaction rate
- 0.173%
- reactions ÷ views · ER floor
- Posts in window
- 41
- of 207 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 39 of 41 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 26 October 2026 |
|---|---|
| Posts held | 207 (3 August 2026 – 26 October 2026) |
| Views total | 305,020 |
| Reactions total | 517 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 26 Oct 2026, 13:03 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
2,224 reactions across 197 posts, in 16 distinct kinds. The most used accounts for 78.6% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 1,747 | 78.6% | |
| 👍 | 260 | 11.7% | |
| 👏 | 75 | 3.37% | |
| 💯 | 45 | 2.02% | |
| 😭 | 20 | 0.899% | |
| ❤🔥 | 15 | 0.674% | |
| ⚡ | 11 | 0.495% | |
| 👌 | 10 | 0.45% | |
| 🤡 | 10 | 0.45% | |
| 😁 | 9 | 0.405% | |
| 🐳 | 8 | 0.36% | |
| 🥰 | 6 | 0.27% | |
| 🫡 | 3 | 0.135% | |
| 🎉 | 2 | 0.09% | |
| 💊 | 2 | 0.09% | |
| 🎄 | 1 | 0.045% |
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 197 of the 207 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 2,224 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 207 most recent posts we hold, published 3 August 2026 to 26 October 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
2026 수출 다변화를 위한 비관세장벽 설명회 : 중국·일본·동남아·서남아를 중심으로 (2026 FTA해외활용지원센터 합동) Keyword#수출 #다변화 #비관세장벽 #관세장벽 #설명회 #중국 #일본 #동남아 #서남아 #FTA 목차 · 중국 · 일본 · 말레이시아 · 태국 · 인도네시아 · 베트남 · 필리핀 · 캄보디아 · 인도
❤4
D램 품귀에 사양 깎는 빅테크… 삼성은 테일러 팹2 '베이스다이' 승부수 DDR4마저 품귀 현상… HBM 설계 변화가 부른 파운드리 반사이익 ◆ 구형 DDR4마저 24% 급등… 물량 부족에 테슬라도 선택한 '디스펙' 고육책 ◆ HBM 적층 단수 하향과 베이스 다이 소요 급증… 美 테일러 팹2 착공 맞물린 삼성 턴키 시너지 https://n.news.naver.com/mnews/hotissue/article/138/0002245894?type=series&cid=2000113
❤5🫡1
삼성전기 MLCC 내년 공급물량만 2조 넘어서, 장덕현 AI 호황에 내년 영업이익 4조 가시권 장덕현 삼성전기 대표이사 사장은 부산, 세종, 베트남 등 기존 공장의 증설을 통해 공급량을 높이는 동시에 국내와 베트남, 필리핀 신공장 건설에도 속도를 낼 것으로 보인다. 25일 삼성전기에 따르면 이 회사가 올해 실리콘 캐패시터와 AI 서버용 MLCC, 인덕터 등으로 체결한 장기공급계약 규모가 4조 원을 넘어선 것으로 추산된다. 이 가운데 내년에 공급하기로 약속한 MLCC 물량만 2조4천억 원을 넘어서는 것으로 파악된다. 또 최근 AI 데이터센터용 MLCC 수요가 폭증하면서 2027년 MLCC 가격은 올해보다 약 20% 더 상승할 것이란 전망이 나온다. 특히 AI 가속기의 사양이 높아지면서 MLCC 탑재량 증가로 이어지는 것으로 파악된다. …
❤9👍3❤🔥2💯2
바이오시밀러 사용 활성화 방안 - 국내 바이오시밀러 시장 분석 - 바이오시밀러 재정영향 분석 - 바이오시밀러 각국 정책현황 [미국] [캐나다] [영국] [EU] [일본] [국내] - 바이오시밀러 활성화 전략
❤9👍4💯3👏1
미국 재무부, 대중국 바이오제약 투자 규제안 발표 (한국바이오협회)
❤3👍2👏1
IAEA "2060년 원자력발전 수요 3배로 급증…AI 확산 영향 " 라파엘 그로시 국제원자력기구(IAEA) 사무총장이 인공지능(AI) 기술 확산과 데이터센터 급증에 따른 폭발적인 전력 수요로 2060년까지 전세계 원자력 발전 수요가 현재의 3배 이상으로 늘어날 것이라고 전망했다. 2025년 기준 전 세계 31개국에서 가동 중인 413기의 원자로가 글로벌 전체 전력의 약 10%, 무탄소 전력의 25%를 담당하고 있으며 현재 15개국에서 72기(77.2GW 규모)의 원자로가 건설중이다. https://n.news.naver.com/mnews/article/001/0016397864?sid=001
❤4⚡2👍1🤡1
[단독] 메모리 쟁탈전에 델이 꺼낸 카드…하청 부품값 11조원 보증 하청 공장이 부품값 못 내면 델이 대신 갚아…美 공시서 확인 구매약정 석 달 새 18조6000억원 급증…1년 반 만에 5배로 마이클 델, 메모리 부족 장기화 경고…내년 이후 물량 확보전 https://www.dailian.co.kr/news/view/1704512/%EB%8B%A8%EB%8F%85-%EB%A9%94%EB%AA%A8%EB%A6%AC-%EC%9F%81%ED%83%88%EC%A0%84-%EB%8D%B8%EC%9D%B4-%EA%BA%BC%EB%82%B8-%EC%B9%B4%EB%93%9C%ED%95%98-2026
❤15👍4💯2🐳1
변압기 다음은 ‘배전’의 시간…전력기기 3사, 美 수주전 2막 열려 AIDC발 전력망 투자, ‘배전기기’ 주문 시작 선두 LS일렉·후발 HD현대일렉 1000억대 수주 잇따라 효성重도 미국서 배전 설루션 소개 https://n.news.naver.com/mnews/hotissue/article/016/0002711813?type=series&cid=2000320
❤22
외국계, 순매수 상위종목 (코스피) 금액기준
👍9👏3❤1
삼성전자 外人 지분율 45.99%…IMF때 수준 외국인 매도세 삼전닉스에 집중 지분율 하락폭, 코스피 1.6배 수준 AI부채 불안 대만도 외인 매도 확산 중소형주·가치·배당주로 분산 주목 https://biz.heraldcorp.com/article/10908386
❤9💯1
세계 원전시장 인사이트 (에너지경제연구원) □현안이슈 •유럽 전력 소매가격과 소비 유연성 분석(ACER·CEER 보고서) 북·남미 • 한미, 미국 내 대형원전 8기 건설 추진 프레임워크 합의 • 미 DOE, Vistra 원전 출력증강·현대화에 최대 5.7조 원 조건부 대출 약정 • 미국 TVA, Clinch River 부지 BWRX-300 건설허가 취득 • 미국 빅테크, 기존 원전 전력구매 및 출력증강 지원 확대 • 캐나다 Saskatchewan 주, 2050년까지 최소 2,600MW 원전 확보 추진 • IAEA·미주개발은행, 중남미·카리브 지역 원자력 협력 MOU 체결 유럽·아프리카 • 폴란드, 원자력발전 프로그램 개정…첫 원전 2036년 상업운전 목표 • 네덜란드, Borssele 원전 계속운전 위한 원자력법 개정안 의회 승인 • …
❤12
Showing the 12 most recent of 207 posts we hold for @Brain_And_Body_Research. 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.
Republishes
Channels on the register whose posts this channel has forwarded.
@ehdwl · 32,00181 posts서화백의 그림놀이 🚀
@easobi · 23,4418 posts루팡
@bornlupin · 48,8577 posts시황맨의 주식이야기
@shmstory · 39,2395 posts에테르의 일본&미국 리서치
@aetherjapanresearch · 34,7893 posts유진투자증권 ETF/파생 강송철
@buykkang · 5,5603 posts그로쓰리서치(Growth Research) [독립리서치]
@growthresearch · 40,1493 posts[메리츠 Tech 김선우, 양승수, 김동관]
@merITz_tech · 24,4843 posts[ IT는 SK ]
@skitteam · 18,1333 posts엄브렐라리서치 Jay의 주식투자교실
@Jstockclass · 26,3552 posts영리한타이거의 리포트 정리🐯
@YoungTiger_stock · 9,1982 postsAWAKE - 실시간 주식 공시 정리채널
@darthacking · 65,2522 postsDS Tech 이수림
@dssemicon · 5,5982 postsKK Kontemporaries
@kkkontemp · 20,8622 posts캬오의 공부방
@Kyaooo · 17,4381 post[한국투자증권 염동찬] 퀀트
@TLTE8EU3QIsyMzM1 · 3,2281 post여의도스토리 Ver2.0-习近平是个狗东西
@YeouidoStory2 · 58,1161 postAI 리서치 딥다이브_Seoul to Wall St.
@aicorporateanalysisdeepdive · 5,6371 post반붐온? 방붐온?
@cpshelter · 5,3941 post석학들의 마켓 (인)사이트 PRO
@getfeed · 8,8071 post인포마켓 infomarket
@infomarketopen · 9,7131 post잠실개미&10X’s N.E.R.D.S
@jake8lee · 17,2391 post[한투증권 김명주] 유통/화장품/생활소비재
@kmj_retailcosmetics · 9,8401 post키움증권 해외선물 톡톡
@kwtok · 9,4421 post스탁이지 - AI 투자 어시스턴트
@maddingStock · 20,6261 post[미래에셋증권 채권/경제] 민지희, 정형기
@miraebond · 6,0771 postPE, M&A, 대체투자, 거버넌스, 책 뉴스
@pef_news · 1,0631 post퀀텀 알고리즘
@quantum_ALGO · 7,6011 post해달의 투자 정보 공유
@seaotterbtc · 30,0531 post지엘리서치_ 독립리서치
@valjuman · 7,2511 post
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 5 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.
Names
Channels on the register whose handles appear in this channel's posts.
@growthresearch · 40,1493 posts[ IT는 SK ]
@skitteam · 18,1333 posts유진투자증권 ETF/파생 강송철
@buykkang · 5,5601 postDS투자증권 리서치
@DSInvResearch · 12,8571 postDS Tech 이수림
@dssemicon · 5,5981 post잠실개미&10X’s N.E.R.D.S
@jake8lee · 17,2391 post[한투증권 김명주] 유통/화장품/생활소비재
@kmj_retailcosmetics · 9,8401 post[미래에셋증권 채권/경제] 민지희, 정형기
@miraebond · 6,0771 post지엘리서치_ 독립리서치
@valjuman · 7,2511 post
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 26 October 2026 — this entry's latest reading, not the date you are reading this.
“Brain and Body Research” (@Brain_And_Body_Research), 34,752 subscribers as measured 26 October 2026. Telegram Register, tgregister.com/channel/Brain_And_Body_Research.
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.