Channel
@free_life59
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
12,537subscribers
+104 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
| Telegram ID | -1001743846586 |
|---|---|
| Type | Channel |
| Username | @free_life59 |
| Description | SNOWBALL EFFECT ⛄️ · 본 채널은 산업 및 기업 스터디 기록용입니다. · 본 채널에서 언급된 종목은 매수/매도 추천이 아닙니다. |
| Created | Between 1 December 2021 and 30 April 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 15 August 2026 |
| Measurements held | 11 |
| Confirmed unchanged | 1 time, most recently 15 August 2026 |
| On Telegram | t.me/free_life59 |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 15 Aug 2026, 05:54 | 12,537 | +10 |
| 14 Aug 2026, 01:04 | 12,527 | +17 |
| 12 Aug 2026, 22:55 | 12,510 | +3 |
| 11 Aug 2026, 23:14 | 12,507 | +20 |
| 11 Aug 2026, 02:14 | 12,487 | +14 |
| 10 Aug 2026, 03:21 | 12,473 | +5 |
| 9 Aug 2026, 01:11 | 12,468 | +6 |
| 8 Aug 2026, 04:13 | 12,462 | -1 |
| 7 Aug 2026, 07:16 | 12,463 | +34 |
| 6 Aug 2026, 09:01 | 12,429 | -4 |
| 6 Aug 2026, 03:19 | 12,433 | first reading |
202 posts held, back to 5 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 18 pagesof Telegram’s post history, 20 posts per page.
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 138 of 202 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 15 August 2026 |
|---|---|
| Posts held | 202 (5 August 2026 – 15 August 2026) |
| Views total | 284,137 |
| Reactions total | 763 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 15 Aug 2026, 12:45 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.
Lifetime counters from Telegram’s own channel header, read 15 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.
Measured directly from 2 videos 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.
696 reactions across 122 posts, in 10 distinct kinds. The most used accounts for 57.9% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 403 | 57.9% | |
| 👍 | 122 | 17.5% | |
| 🔥 | 42 | 6.03% | |
| 😱 | 38 | 5.46% | |
| 🤔 | 31 | 4.45% | |
| 😭 | 27 | 3.88% | |
| 👏 | 19 | 2.73% | |
| 🫡 | 9 | 1.29% | |
| 😢 | 3 | 0.431% | |
| 💯 | 2 | 0.287% |
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 138 of the 202 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 763reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 202 most recent posts we hold, published 5 August 2026 to 15 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.
#AI #메모리 1. AI 에이전트의 확산으로 인한 메모리 상태 유지 및 데이터 처리 수요의 기하급수적 증가. 2. 2027년 글로벌 HBM 수요가 약 486억 Gb(48.6bn Gb) 수준까지 폭증할 것이라는 모건스탠리의 전망. 3. 연산 성능보다 메모리 공급 능력이 AI 레이스의 승패를 결정하는 핵심 병목으로 작용함. Building new memory fabs takes years, not a few months. That means the AI race isn’t simply about who can build the fastest GPU anymore, it’s increasingly about who can secure enough memory to keep those GPUs fed.
❗️AI has a memory problem AI companies can keep buying faster chips. The problem is, those chips are only useful if they have enough ultra-fast memory to feed them. That memory is called HBM, High Bandwidth Memory. It sits right next to AI processors and moves data at ridiculous speeds, keeping the chip busy instead of making it wait around for information. And demand is about to go absolutely crazy. Morgan Stanle…
#ISM #전략 #외국인 1. 미국 제조업 경기 확장 + 물가 둔화 → 달러 약세 및 외국인 국내 증시 유입에 우호적 환경 형성. 2. 삼성전자 반등 가능성. 주가 할인율 급등과 외국인 지분율 급락으로 수급 부담 완화, 고성장주에서 고배당주로 재평가 가능성 부각. 3. 과거 애플 사례처럼 성장 둔화 이후 배당·자사주 매입 강화 → 밸류에이션 재평가 가능. 삼성전자 주주환원 확대 여부가 핵심. 4. 외국인은 향후 이익 개선을 선반영할 가능성 → 2027년 순이익 증가율 및 최근 추정치가 상향되는 기업 선호. 5. 주요 후보는 삼성전기, 현대차, 삼성바이오로직스, 한화에어로스페이스, 삼성물산, HD현대일렉트릭, HD한국조선해양, 한미반도체, 카카오, 현대건설 등.
❤5
8/18일 하나증권 전략 이재만 [화수분전략] 외국인은 무엇을 살까 ▶자료: https://bit.ly/4hAgsFN * 미국 제조업 경기 확장 확인 이후 물가까지 하락. 연준의 기준금리 인상 우려는 완화, 경기는 확장하고 있어 미국 장단기금리차(10년물-2년물)는 반등 이어감 * 미국 2년물 국채금리가 하락하고, 장단기금리차 상승 국면에서 달러인덱스의 전월 대비 하락 폭은 상대적으로 가장 크고, 하락 확률도 가장 높음. 달러 약세를 기반으로 한 국내 증시로의 외국인 자금 유입 기대 * 최근 들어서는 삼성전자가 고성장주에서 고배당주로 변화할 수 있다는 기대도 높아지고 있음. 과거 애플의 경우 2010~12년 순이익 증가율이 70%를 넘는 성장주, 3년 동안 주가가 110%나 상승(S&P500 23%)하며 시가총액 1위 등극 * 2013~…
모델 생태계를 확대해서 자기강화. 그리고, 모델 경쟁에서 컴퓨팅 경쟁으로 넘어가는 방향?
[알리바바 Qwen 오픈 모델, 6개월간 글로벌 다운로드 30억건 돌파하며 메타와 구글을 제치고 오픈 AI 생태계 선두로 부상](https://www.bloomberg.com/news/articles/2026-08-15/alibaba-ai-models-hit-3-billion-downloads-passing-meta-google) ◦ 알리바바 Qwen, 글로벌 오픈 AI 모델 다운로드 1위 등극 • 알리바바의 오픈 웨이트 AI 모델은 최근 6개월간 글로벌 누적 다운로드 30억건 이상을 기록. • 메타, 구글 및 중국 내 경쟁 모델들을 제치며 세계 최대 규모의 오픈 AI 모델 생태계로 부상. • Hugging Face 자료에 따르면 2026년 구글 오픈 모델 다운로드는 4억1,800만건, 메타는 2억2,700만건. • → Qwe…
❤1
#투자 #앙드레코스톨라니 #경험
투자자는 기자나 의사라는 직업과 다음 한 가지 면에서 뚜렷하게 구분된다. 그것은 학교에서 배울 수 없다는 것이다. 그의 무기는 첫째도 경험이고 둘째도 경험이다. 나는 80여 년간 증권계에서 쌓아온 내 경험을 내 체중과 맞먹는 금하고도 바꾸지 않을 것이다. 내 경험은 크나큰 손실을 겪으면서 얻은 것이다. 그러므로 투자자들 가운데 일생에 적어도 두 번 이상 파산하지 않은 사람은 투자자라고 불릴 자격이 없다고 생각한다. <돈, 뜨겁게 사랑하고 차갑게 다루어라> 앙드레 코스톨라니
❤4👍4
예시를 들자면 어업을 함에 있어서 법적으로, 또 산업 생태계의 도의적 관점에서도 아주 어린 물고기까지 씨를 말리는 것은 금기시 된다. 단기적으로는 특정 주체의 이익이 되겠지만, 장기적으로는 해양 생태계의 건전성을 파괴하고 결과적으로 어부들의 산업 지속가능성이 현저하게 저하하기 때문이다. LTA도 마찬가지로 볼 수 있겠다. 공급자들 입장에서 규율없이 높은 가격을 청구한다면 단기적으로는 큰 이익이 되겠지만, 중장기적으로는 앞으로 살 찔 물고기를 모두 미리 죽이는 꼴이 된다. 때문에 현 구간에서는 높은 수요에도 불구하고 메모리 공급사들이 자신들의 단기적 이익 일부를 양보하는 것으로 볼 수 있다. 특히나 현재 AI 산업에서 가장 중요한 역할을 하는 데이터 센터 인프라 내 칩의 BOM은 과반 이상을 차지하기 때문이다. AI 수요가 좋다는 가정하에…
https://m.blog.naver.com/tmdejr1267/224379483437 #Seung
#독서 #투자의명문들 무언가에 확신이 있으면서도 (집중) 오류가 있거나 더는 시대에 맞지 않다고 밝혀진 생각을 흔쾌히 포기하는 태도(겸손)보다 더 강력한 능력은 거의 없다.
❤4
Situational Awareness, 레오폴드 아셴브레너(Leopold Aschenbrenner) 2분기 13F 보고서를 제출 보유 비중 상위 5개 종목 (Top 5 Positions) * 샌디스크 $SNDK: 28.52% * 마이크론 $MU: 28.01% * 블룸에너지 $BE: 9.54% * TSMC $TSM: 6.36% * 네비우스 $NBIS: 6.20% * 주요 매수 종목 (Top Buys): $MU, $SNDK,$TSM, $NBIS, $STM * 주요 매도 종목 (Top Sales): $SMH 풋, $NVDA 풋, $ORCL 풋, $AVGO 풋, $AMD 풋 * 신규 편입 종목 (New Positions): $NBIS,$STM, $VSH,$CBRS 상위 25개 포지션 (Top 25 Positions) - …
❤3
Showing the 12 most recent of 202 posts we hold for @free_life59. 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 — 48,979 of 1,481,346entries 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.
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.
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.
Named by 3 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.
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.
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 15 August 2026 — this entry's latest reading, not the date you are reading this.
“프리라이프” (@free_life59), 12,537 subscribers as measured 15 August 2026. Telegram Register, tgregister.com/channel/free_life59.
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.