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Channel

Machine Learning Lab.

@machine_learning_lab

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

875subscribers

+1 since we began measuring on 9 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1001809590506
TypeChannel
Username@machine_learning_lab
CreatedBetween 1 October 2022 and 30 September 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded9 August 2026
Last confirmed live10 August 2026
Measurements held2
Confirmed unchanged1 time, most recently 10 August 2026
On Telegramt.me/machine_learning_lab

Growth

874875874.59 Aug 2026, 17:02 — 874 subscribers10 Aug 2026, 12:04 — 875 subscribers9 Aug 2026, 17:0210 Aug 2026, 12:04
2 measurements taken within a single day, net +1. 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 874–875 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
10 Aug 2026, 12:04875+1
9 Aug 2026, 17:02874first reading

Engagement

13 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 1 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
55.9%
avg views ÷ 875 subscribers
Avg views / post
489
10 posts measured
Reaction rate
1.19%
reactions ÷ views · ER floor
Posts in window
10
of 13 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
WindowRolling 30 days · latest post in window 4 August 2026
Posts held13 (4 July 20264 August 2026)
Views total4,889
Reactions total58
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken9 Aug 2026, 17:02 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

74 reactions across 13 posts, in 8 distinct kinds. The most used accounts for 31.1% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
2331.1%
🔥1824.3%
👍1723.0%
👏912.2%
🤔34.05%
🤣22.70%
💯11.35%
😁11.35%

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 13 of the 13 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 74reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 13 most recent posts we hold, published 4 July 2026 to 4 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

4 Aug 2026, 09:40 UTC268 views2 reactionsread 9 August 2026
Forwarded from @chatwakilAIPhoto

⚖️YURIDIK SOHADA SUN’IY INTELLEKT: XAVFMI YOKI YANGI IMKONIYAT? 📅 2026-yil 3-avgust kuni Adliya vazirligi va Wakil AI hamkorligida soha mutaxassislari hamda yuristlar uchun dolzarb mavzuda seminar-trening bo‘lib o‘tdi. Huquq sohasi vakillari to‘plangan ushbu tadbir «Yuridik sohada sun’iy intellektdan mas’uliyatli foydalanish va prompt muhandisligi: Etikasi · Yutuqlari · Xavflari · Amaliy ko‘nikmalari» mavzusiga bag‘

1🔥1

3 Aug 2026, 17:01 UTC309 views6 reactionsread 9 August 2026

​​🤖 Alibaba'dan yangi gigant: Qwen3.8-Max Alibaba'ning Qwen jamoasi bugun Qwen3.8-Max'ni rasman taqdim etdi — bu hozirgacha Qwen oilasidagi eng qudratli model. Model 2,4 trillion parametrli mixture-of-experts (MoE) arxitekturasida qurilgan, biroq har bir so'rovda taxminan 95 milliard parametr faollashadi — bu uni real ishlatish uchun ancha samarali qiladi. Kontekst oynasi 1 million tokengacha, matn, rasm va videoni

3🔥2👍1

25 Jul 2026, 14:07 UTC538 views5 reactionsread 9 August 2026
Photo

Tanishing Opus 5! O’rtoqlar nima bo’lyapti ey!!! 👉 @machine_learning_lab 👈

🔥41

25 Jul 2026, 05:31 UTC525 views4 reactionsread 9 August 2026

​​Xitoyning Kimi K3: eng katta ochiq manbali model Xitoylik Moonshot AI kompaniyasi Kimi K3 nomli modelni e'lon qildi — bu hozirgacha chiqarilgan eng katta ochiq manbali (open-source) AI modeli, 2,8 trillion parametrga ega. Model Arena.AI'ning Frontend Code reytingida birinchi o'rinni egalladi, hatto Anthropic va OpenAI'ning ba'zi modellaridan ham o'zib ketdi. Moonshot'ning o'zi ta'kidlashicha, K3 hali ham Claude Fa

🔥31

24 Jul 2026, 18:05 UTC622 views12 reactionsread 9 August 2026
Photo

Arsenal FC ga AI muhandis kerak ekan. 😄 Topshirib ko’rsa arziydi. Manchester United, City, Liverpool, Chelsea muhlislariga jo’natib qo’yasizlar. Ayg’oqchilik qilishlari ham mumkinda 😉 👉@machine_learning_lab 👈

👏9🤣21

23 Jul 2026, 14:09 UTC456 views4 reactionsread 9 August 2026

Google uchta yangi Gemini modelini taqdim etdi 21-iyul kuni Google DeepMind uchta yangi modelni e'lon qildi: Gemini 3.6 Flash, 3.5 Flash-Lite va xavfsizlikka ixtisoslashgan 3.5 Flash Cyber. Kompaniyaning rasmiy blogiga ko'ra, 3.6 Flash 3.5 Flash'ga nisbatan chiqish tokenlarini 17 foizga kamaytiradi (ba'zi benchmarklarda 65 foizgacha), narxi ham pasaygan — chiqish narxi 1 million token uchun 9 dollardan 7,5 dollarga

👍2🔥2

22 Jul 2026, 12:16 UTC432 views12 reactionsread 9 August 2026

​​Ochiq vaznli modellar frontier modellarni siqib chiqaryaptimi? TechCrunch'ning yangi tahliliga ko'ra, ochiq vaznli (open-weight) AI modellari yopiq frontier modellardan tezroq o'sib bormoqda. Hugging Face ma'lumotlariga ko'ra, bu bahorda xitoylik ochiq modellar platformadagi yuklab olishlarning 41 foizini tashkil etgan — bu AQSh modellaridan ko'proq. OpenRouter'da eng mashhur oltita model Tencent, Xiaomi, DeepSeek

👍73🔥1😁1

20 Jul 2026, 12:14 UTC515 views5 reactionsread 9 August 2026

​​Apple va OpenAI o'rtasidagi tijorat sirlari mojarosi 10-iyul kuni Apple Kaliforniya federal sudida OpenAI'ga qarshi tijorat sirlarini o'g'irlash bo'yicha da'vo qo'zg'atdi. Asosiy ayblanuvchilardan biri — OpenAI'ning apparat ta'minoti bo'yicha rahbari Tang Tan, u Apple'da 24 yil ishlab, iPhone va Apple Watch dizayni bo'yicha vitse-prezident lavozimigacha ko'tarilgan edi. Da'voga ko'ra, Tan va yana bir sobiq Apple m

4🤔1

15 Jul 2026, 10:47 UTC666 views3 reactionsread 9 August 2026
Forwarded from @iqtisodchi_kundaligiPhoto

Sun’iy intellekt yo‘nalishida yangi mahsulot yaratayotgan jamoalar uchun 1 000 000 dollarlik «President AI Award 2026» tanlovi e’lon qilindi Aynan sun’iy intellekt yechimlari bilan shug‘ullanuvchi jamoalar uchun «President AI Award 2026» tanloviga hujjatlar qabul qilinmoqda. Uning doirasida davlat boshqaruvi, tibbiyot, ta’lim, sanoat va yashil iqtisodiyot sohalaridagi 15 ta eng yaxshi loyihaga 40 000 dollardan 100 0

👍21

15 Jul 2026, 05:17 UTC558 views5 reactionsread 9 August 2026
Forwarded from @uzbekonomics

Kuni kecha yuzlab nufuzli iqtisodchilar, olimlar ochiq xat yozishibdi. Masalan, Acemoglu, Autor, Milgrom, Stiglitz, Akerlof, Aghion, Krugman, Bernanke, Furman va boshqalar unga qo'l qo'yishgan. Xatni mazmuni juda qisqa: AI keyingi 10 yilda tubdan kuchayishi mumkin, sanoat inqilobidan ham kattaroq, lekin ancha tezroq iqtisodiy o'zgarishlarni keltirib chiqarishi mumkin, millionlab ish o'rinlari xavf ostida, lekin turm

2🤔2👍1

13 Jul 2026, 05:43 UTC515 views6 reactionsread 9 August 2026
Forwarded from @kunuzPhoto

“Sun’iy intellekt qadriyatli insonni yenga olmaydi” – ekspert bilan suhbat Olimlar sun’iy intellekt rivoji uch bosqichdan iborat bo‘lishini aytadi. Hozirgi birinchi bosqich – har biri alohida yo‘nalishlarga ixtisoslashgan chatbotlar davri. Janubiy Koreyadagi Gachon universiteti sun’iy intellekt professori Jumabek Alixonov Kun.uz bilan suhbatda SIning mehnat bozoriga ta’siri va texnologiyaning keyingi avlodlari qanda

2🔥2👍1💯1

6 Jul 2026, 07:36 UTC≈1,370 views7 reactionsread 9 August 2026

🧬 Claude Science — olimlar uchun yangi AI ish maydoni Anthropic o'z Claude modellari asosida ilmiy tadqiqotchilar uchun maxsus mo'ljallangan yangi ilova — Claude Science'ni taqdim etdi. Bu yangi model emas — xuddi hammaga tanish Claude (jumladan Opus 4.8) asosida ishlaydi, ammo tadqiqotchilarning kundalik ish jarayonini butunlay o'zgartirish uchun yaratilgan. 🔬 Nima qila oladi? • Genomika, yagona hujayra tahlili,

3🔥3👍1

Showing the 12 most recent of 13 posts we hold for @machine_learning_lab. 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 — 437,012 of 1,151,006entries 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 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.

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.

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 10 August 2026 — this entry's latest reading, not the date you are reading this.

“Machine Learning Lab.” (@machine_learning_lab), 875 subscribers as measured 10 August 2026. Telegram Register, tgregister.com/channel/machine_learning_lab.

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.