一般来说,口感偏好有喜欢嫩口感和喜欢柴口感的。我是前者,所以觉得新品猪猪堡很好吃,面包是软的,猪肉饼是嫩的。

Channel
搞机日记
@gaojiriji
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Citations · Cite this entry
8,351subscribers
+3,265 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
Register entry
| Telegram ID | -1001293289931 |
|---|---|
| Type | Channel |
| Username | @gaojiriji |
| Created | 24 March 2018 — measured — cross-checked against a third-party dataset (TGDataset) |
| First recorded | 6 August 2026 |
| Last confirmed live | 16 September 2026 |
| Measurements held | 15 |
| Confirmed unchanged | 1 time, most recently 16 September 2026 |
| On Telegram | t.me/gaojiriji |
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 12 September 2026 and assigned it the closest of 31 fixed categories, at 97% 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.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 16 Sept 2026, 21:59 | 8,351 | +4 |
| 13 Sept 2026, 00:56 | 8,347 | +127 |
| 9 Sept 2026, 00:38 | 8,220 | -28 |
| 3 Sept 2026, 22:00 | 8,248 | -10 |
| 31 Aug 2026, 19:44 | 8,258 | +3 |
| 28 Aug 2026, 18:16 | 8,255 | -6 |
| 25 Aug 2026, 14:33 | 8,261 | +18 |
| 22 Aug 2026, 09:45 | 8,243 | +19 |
| 19 Aug 2026, 08:37 | 8,224 | +1,199 |
| 16 Aug 2026, 17:47 | 7,025 | +1,941 |
| 12 Aug 2026, 23:33 | 5,084 | -2 |
| 9 Aug 2026, 19:01 | 5,086 | -1 |
| 7 Aug 2026, 04:02 | 5,087 | +1 |
| 6 Aug 2026, 04:16 | 5,086 | no change |
| 6 Aug 2026, 04:08 | 5,086 | first reading |
Engagement
20 posts held, back to 21 March 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 pages of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 24 August 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
- Video runtime
- 10s
- Average length
- 5s
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.
Reaction mix
164 reactions across 15 posts, in 14 distinct kinds. The most used accounts for 36.6% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 😁 | 60 | 36.6% | |
| ❤ | 48 | 29.3% | |
| 👍 | 33 | 20.1% | |
| 😇 | 6 | 3.66% | |
| 🌚 | 3 | 1.83% | |
| 🕊 | 3 | 1.83% | |
| 🤷♂ | 3 | 1.83% | |
| 👏 | 2 | 1.22% | |
| 🐳 | 1 | 0.61% | |
| 👎 | 1 | 0.61% | |
| 👻 | 1 | 0.61% | |
| 💩 | 1 | 0.61% | |
| 🗿 | 1 | 0.61% | |
| 🤗 | 1 | 0.61% |
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 16 of the 20 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 164 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 21 March 2026 to 24 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
说到耗电太凶,同事提示我用最不透明一档的液态玻璃会减少发热更加流畅。 我将信将疑,调到最不透明的一档仔细看,发现模糊效果已经是「减弱动态效果」级别的了。(此前说过液态玻璃的边缘折射效果是一种动画) 四张图前两张是液态玻璃滑块调节到最右,后两张是开启减弱动态效果后的模糊效果。Telegram压缩可能看不太出来,就是一种能看出色块的劣质模糊效果。
❤4
除了不太稳定的动画帧率,iOS 27 beta 就剩下这个恶心的硬黑边了,但是仔细观察的话黑边里的模糊是渐进式的,可能未来的版本里会去掉黑边只留模糊,就像照片App一样。 beta 5耗电太凶了。
❤3🌚3
液态玻璃完全体。
❤11👎1
beta 5 拓展了液态玻璃两端的极限,修复了最透明玻璃下的超明显锯齿问题。不过应该也因设备而异。 目测是A17 Pro之前的机器都还带有明显锯齿。
今天又被某些国产模型浇了冷水。在一个国产在线文档产品里面对AI说了一句「去掉所有多余空行」,这个模型居然用英文思考了三分钟又用中文思考了很久,久到我发完这条都没思考完,还多次调用mcp,依然没有搞定。所有思考的过程基本就是 ummm wait unless but wait but wait wait so wait final final 无限纠结,不敢反驳用户「我没看到多余空行啊」显得自己很蠢,陷入了无尽的循环…… 是模型智能太低又把思考拉满的结果吗?先去吃个饭,回来看看它到底能纠结多久。地球母亲啊,原谅我,泡面不等人。 update:吃完饭了,没有检测出空行。
😁30🕊3
之前碰到有个神秘问题:每一次重启后,我的 Jump Desktop Connect 就会卡在初始化动不了,一开始我以为是软件的bug或者是 macOS 27 beta 的bug,但是重新安装后并没有解决,所以我让 DeepSeek V4 Flash/ Big Pickle去解决这个问题。 这些小模型的回复是,软件的 launch 进程失败了,所以帮我写了一个 plist,我一看真启动成功了,真棒!但是我第二次重启发现问题依然在。这次我找了 GPT terra high,它先拟了三个请求去互联网上查询类似的问题,最后给了我这样的回答。 我很意外。我确实记得因为没认出 PhaseFive Systems 是哪个软件从而关掉了它的后台运行权限……去设置里开了就好了。 PS:最近 all in GPT,terra就很棒了,是几百K token 就能帮我搞定日常小问题还是一次过的了。而且 5.6 给我感觉在 work/codex 里…
❤7👍2
受这件事情,最近一个月喜欢用小模型干活,V4 Flash类型的那种,什么国产模型匿名模型都在用。只有复杂的嵌套任务才会用 GLM 5.2( K3 出来后GLM都显得慢了)。 比较有意思,我发现小模型在目前普遍的harness下基本都能乖乖老实干活,只是偶尔会犯蠢——不知道怎么做傻在原地思考打转、自作主张用自己的方法尝试忽略原文档等等。这时候只要插嘴一句就能让它继续做下去。这已经不是实习生了,更像是班主任去差使高中生干杂活。 我觉得大部分人想让模型完成的就是这些脏活累活。如果这个提点的动作不是人来完成,而是让更聪明、更大参数量的模型来扮演班主任,会更加无感。
👍2❤1
跟前几年的情况类似,beta 1 像一个分支的产物,打个样给WWDC后的营销用。后面的 beta 2 和 3 像是另一个分支的东西,汉化都统统还回去了,根据WWDC后的用户反馈重新开发?做到差不多 beta 1 的稳定性后就推送个公测版。 后面 beta 4 beta 5 可能才会稍微更稳定一些。 怀念 nugget,如果想升级 iOS 27 测试版的话,记得在 iOS 26 上用 nugget 干掉遥测再上,iOS 27 测试版目前暂不支持用 nugget了。
https://fixupx.com/sunnny1583/status/2075796043195994317 iOS 27 到 beta 3 一直在微调液态玻璃滑块,现在回到了类似 beta 1 的状态,最透明的情况下文字和图标边缘会产生明显的锯齿很不美观;而且可读性差劲。 PS:我觉得默认一档的液态玻璃是最漂亮的。现在还解决了液态玻璃动画连续性的问题(比如音乐app中缩放播放界面最后一帧)。 喜欢透明质感的话还是需要往回拉一点加点模糊。 目前还是不建议升级 beta,一想到还有两个月的bug要品尝😑每天跑几十M的log。
❤1
某些大模型现状:纯烧token,不产出。地球母亲何时惩罚?
😁15
iOS 27 beta 2 不出意外改动又比较大。 beta 1 的时候除了漫山遍野的index未完成哀嚎,还有一大堆KOL吹嘘续航和性能双提升。但是在我看来,这个在官网与 26.4.2 版本对比的 beta 1 还是太早期了: 1、液态玻璃透明档背后是能看出很明显的锯齿状的。 2、低电量模式下的流畅度还不如 26.6 beta。 3、也没觉得续航有什么提升,无论是否索引完。 作为第一个beta是比较出色了,但是说「比 iOS 26 正式版bug还要少」就有点太过了。言归正传,beta 2 这次: 1、液态玻璃又大改了一版本参数,没有明显的背景采样锯齿了,相应地玻璃的边缘折射感也少了(可以对比一下小角)。没有锯齿感的话就可以放心开最透明一档了,特别会影响可读性的场景(比如控制中心)苹果也做了兜底,不会真的透。 2、性能和续航都感觉更好了一点,尤其是低电量模式下。也可能是错觉,因为我也经历过好几次刚升级完感觉不错、两周后又开始…
❤7👏2😁1
Showing the 12 most recent of 20 posts we hold for @gaojiriji. 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.
Posts edited after publishing
@gaojiriji edited 1 post after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
- First edit seen
- 18 August 2026
- Most recent edit
- 18 August 2026
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.
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 1 registered channel — 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 16 September 2026 — this entry's latest reading, not the date you are reading this.
“搞机日记” (@gaojiriji), 8,351 subscribers as measured 16 September 2026. Telegram Register, tgregister.com/channel/gaojiriji.
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.