Telegram RegisterThe public register of Telegram

Channel

小声读书 🙈

@weekly_books

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

38,035subscribers

-9 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-1001134924499
TypeChannel
Username@weekly_books
Description在喧嚣的 AI 浪潮中,我们选择回到最朴素的成长逻辑:通过阅读沉淀思考,通过思考驱动行动,最终在技术的折叠中,重塑个体的厚度。
Created30 August 2017measured — cross-checked against a third-party dataset (TGDataset)
First recorded6 August 2026
Last confirmed live13 August 2026
Measurements held8
Confirmed unchanged1 time, most recently 13 August 2026
On Telegramt.me/weekly_books

Growth

38,03238,04838,0406 August 2026 — 38,044 subscribers6 August 2026 — 38,048 subscribers8 August 2026 — 38,041 subscribers9 August 2026 — 38,044 subscribers10 August 2026 — 38,037 subscribers11 August 2026 — 38,033 subscribers12 August 2026 — 38,032 subscribers13 August 2026 — 38,035 subscribers38,0356 August 202613 August 2026
8 measurements spanning 7 days, net -9. 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 38,030–38,050 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
13 Aug 2026, 08:1538,035+3
12 Aug 2026, 08:0238,032-1
11 Aug 2026, 05:1438,033-4
10 Aug 2026, 04:4838,037-7
9 Aug 2026, 05:0138,044+3
8 Aug 2026, 01:4138,041-7
6 Aug 2026, 22:2238,048+4
6 Aug 2026, 03:4538,044first reading

Engagement

25 posts held, back to 4 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 19 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
14.9%
avg views ÷ 38,035 subscribers
Avg views / post
5,670
19 posts measured
Reaction rate
0.646%
reactions ÷ views · ER floor
Posts in window
19
of 25 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 16 of 19 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 10 August 2026
Posts held25 (4 July 202610 August 2026)
Views total107,790
Reactions total605
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken14 Aug 2026, 00:51 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
625
Videos
9
Links
957

Lifetime counters from Telegram’s own channel header, read 14 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.

Reaction mix

696 reactions across 22 posts, in 15 distinct kinds. The most used accounts for 23.1% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
16123.1%
😡9313.4%
🖕669.48%
👍649.20%
🍌608.62%
😈527.47%
👎466.61%
🥱395.60%
💩344.89%
🤡334.74%
👏263.74%
🌚142.01%
😱40.575%
😁20.287%
🤔20.287%

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 22 of the 25 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 696reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 25 most recent posts we hold, published 4 July 2026 to 10 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.

Recent posts

10 Aug 2026, 04:24 UTC≈3,300 views4 reactionsread 14 August 2026
Photo

这篇写的不错,纯手码字。 手上这套 Za Bank + Wise + Starryblu + N26 + Schwab 的方案越用越顺手,加上 Plasma 和 Nerverless,几乎完美了。 https://mp.weixin.qq.com/s/Az2eGiCHWBIdSz0N8OmnoQ

👍31

Signed mastergo

9 Aug 2026, 07:27 UTC≈3,890 views39 reactionsread 14 August 2026

建议大家,都要注意「用脑卫生」 最近越来越觉得,现代人除了注意个人卫生,也应该注意用脑卫生。 什么叫「不卫生」? 第一,没睡好。大脑像手机一样,电都没充满,就开始高强度运行。 第二,频繁多任务切换。一会儿微信,一会儿刷信息,一会儿工作,每次切换都在消耗注意力和执行功能。 第三,信息过载和决策疲劳。AI 时代尤其严重,每天接收的信息太多,知道得越来越多,脑子反而越来越乱。 第四,长期压力和压抑情绪。持续应激会影响情绪、记忆和判断。 第五,长期高糖、高度加工饮食,会增加代谢负担、氧化应激和慢性炎症。 真正的「用脑卫生」其实很简单: 睡眠第一位,坚持深度工作,规律运动,适当冥想,学习一些真正困难的新东西,多吃蔬菜、鱼类、坚果和优质脂肪,多接触自然。 大脑和身体一样,需要恢复,也需要训练。 很多时候,你并没有变笨。 只是你的大脑,真的该「洗个澡」了。🧠

38👏1

Signed mastergo

9 Aug 2026, 00:57 UTC≈3,810 viewsread 14 August 2026

在笔记本里运行 Kimi-K3 https://github.com/FareedKhan-dev/kimi-k3-in-c

Signed mastergo

8 Aug 2026, 06:32 UTC≈4,050 viewsread 14 August 2026

状态栏里面的猫猫 https://github.com/runcat-dev/RunCatNeo

Signed mastergo

8 Aug 2026, 01:27 UTC≈4,200 views30 reactionsread 14 August 2026
Photo

谷歌的 Gemini 模型慢慢变更好用了,对应的 macOS 客户端,体验很好。最近加入了 Spark 功能,可以定时执行各类任务。 https://gemini.google/mac

👎27🤔21

Signed mastergo

3 Aug 2026, 01:19 UTC≈6,550 views10 reactionsread 14 August 2026

Pi 配上 DeepSeek 的 v4 Flash 模型,是我这一个月用下来,在速度、性能和价格上找到的最优解。 我实测实时最高速度能达到 100 token/s,日常平均在 60 到 80 token/s。 https://www.ssgoo.net/pi-guide

10

Signed mastergo

1 Aug 2026, 15:29 UTC≈5,910 views1 reactionsread 14 August 2026
Photo

周末玩 9Router 和 AnySearch 不亦乐乎,索性把它们集成到挖掘机里面了。挖掘机完全免费,针对中国地区做了特别 CDN 优化,网页秒开,开箱即用。🚀 https://mastersgo.cc 点击右上角的【模型设置】按钮,切换到「本机 Cli 」就能看到 9Router 的选项,填入密钥就能愉快玩耍了。 点击右上角的【模型设置】按钮,往下滑一点就能看到 AnySearch 的选项,30 秒就能完成配置。 我使用 Claude Fable 5 模型重构了「股市挖掘机」,作为我的个人量化分析工具,已经完全免费开放使用,从中挖掘各类投资机会。任何新股买入之前务必请你的 AI 老师分析一下。

1

Signed mastergo

1 Aug 2026, 00:46 UTC≈5,410 views16 reactionsread 14 August 2026
Photo

Gemini Spark 上线了……以前搜新闻、整理、写稿再存 Drive 一整套流程搞半天,现在扔个指令全自动干完,全程不用人碰🫨 本质上就像 Google 直接给你送了一台云主机,24 小时在后台跑 Agent,能拆解任务还能深度整合 Google 全家桶。 https://gemini.google.com/spark

👍142

Signed mastergo

30 Jul 2026, 12:39 UTC≈5,390 views16 reactionsread 14 August 2026

整个七月,市场到底发生了什么?🤔 第一层:上游买不动了。过去两年定价极简:算力稀缺 → 谁多花钱谁有未来。市场奖励 Capex。现在买家要看折旧、自由现金流和单位算力回报。Meta 外售闲置算力一类信号,把「绝对稀缺」戳出裂缝;龙头业绩可以很好,股价仍可能杀。 第二层:应用侧缺第二张成绩单。vibe coding、Agent 工作流虽然显著提升效率,也有真实付费。可 AGI 仍在远期,还缺能横向复制、规模化吃毛利的超级场景。自动驾驶、机器人等场景距离爆发都还比较久远。🤡 第三层:机械杀。TMT 动量、配对交易、「多半导 / 空云」一类拥挤仓,碰上多策略同步降风险,跌得齐、跌得快。 我现在还是两周前的策略。👇 顶是尖的,底是圆的。不要杠杆,不要融资,不要加仓。拿着筹码和现金,等科技真正止跌。先看全球定价锚(半导 / AI 链)稳住,再谈 A 股右侧。信号没来,就不动。 至于消费、石油等板块,对我来说不够有吸引力,也不具

👏94👍3

Signed mastergo

26 Jul 2026, 02:57 UTC≈6,660 views11 reactionsread 14 August 2026

AI 产业股票池项目已经开源 👇 https://github.com/yaoleifly/ai-stock-pool 支持用户一键部署到 Vercel 或者 Cloudflare 上,你们也可以 fork 过去二次开发。🤝

👍101

Signed mastergo

Showing the 12 most recent of 25 posts we hold for @weekly_books. 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 — 541,789 of 1,183,361entries 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

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.

Mentions

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.

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.

“小声读书 🙈” (@weekly_books), 38,035 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/weekly_books.

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.