Channel
@otabekswe
On this record: Growth · Engagement · Posts · Citations · Cite this entry
2,840subscribers
-5 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
| Telegram ID | -1001855742029 |
|---|---|
| Type | Channel |
| Username | @otabekswe |
| Created | Between 1 October 2022 and 30 September 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 13 August 2026 |
| Measurements held | 4 |
| Confirmed unchanged | 1 time, most recently 13 August 2026 |
| On Telegram | t.me/otabekswe |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 13 Aug 2026, 04:24 | 2,840 | -6 |
| 10 Aug 2026, 05:11 | 2,846 | +1 |
| 6 Aug 2026, 21:11 | 2,845 | no change |
| 6 Aug 2026, 20:46 | 2,845 | first reading |
20 posts held, back to 9 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 2 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.
| Window | Rolling 30 days · latest post in window 26 July 2026 |
|---|---|
| Posts held | 20 (9 March 2026 – 26 July 2026) |
| Views total | 9,940 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 7 Aug 2026, 16:07 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.
Ushbu darslar hayotimga quvonch olib kelgan. Amerika, Yevropa va hatto Avstraliyada o‘quvchi talabalarning vaqtini saqlab qolibdi. FAANG kompaniyalariga ishga kirishda ham bir necha bor yordami tegdi. Ularni ishga taklif olganiga guvoh bo‘lganman. Sizga ham foydasi tegsin, esingizdan chiqqan bo‘lsa eslatay degandim. O‘qing!
AI modellar quryabmiz. Eng katta olgan xulosalarim: 1. Hozirgi modellarda deyarli arxitektura tomonlama o’zgarish yo’q. 2. Yaxshilanishlar data labeling va reinforcement learning muhiti yaratuvchi kompaniyalar xisobiga bo’layabdi. 3. Fable, Sol ham shunchaki bir sohaga fine-tune (yoki CPT) qilingan chuqur. Ammo modellar o’zgarmasa ham boshqa jarayonlar o’zgarayabdi: 1. Deyarli ko’p agentlar qurgan dasturlada ochiq…
O'zbek tilida ravon so'zlashuvchi sun'iy intelekt qurishimizda hissa qo'shing. Qanday deysizmi? Yo berilgan matnni o'qib, yoki o'qilgan matn audiosini tekshirib. hissa.voicelab.uz @voicelab_uzbot Tez kunda yangiliklarimiz ko'payadi.
#startup Texnik qiyin ammo juda katta impact keltiruvchi loyiha qilmoqchimisiz? Sizga men ko'rgan va topgan qiziq muammolarni aytaman. Bular multi-billion dollar startup idealar 1. GPU isolation: CPU uchun hardware va software level da deyarli ko'plab ishlar qilingan. Ammo GPU larni multi-tenant muhitda ishlatish va izolyatsiya qilish bo'yicha effektiv yechimlar halicha yo'q (shaxsan men ko'rmadim). AI kompaniyala…
#offTopic #startup Ishdan ketib to'liq startap qilish tomon o'tar ekanman ba'zi qiziq narsalarni topdim, va ularni shu yerda yozmoqchiman. Agar siz ham startap qilmoqchi bo'lsangiz, bular haqida albatta o'ylab ko'ring. Investitsiya juda katta tuzoq. Investorlar "biz founderga pul tikamiz" deyishadi, lekin bir qop qog'oz va biznes haqida ma'lumot so'rashadi. To'g'ri risk qilishni hamma ham yoqtirmaydi, ammo so'zlar…
#experience Hamma vibe coding qilayabdi. Bilasizmi, korxona ko'p maxsulot ishlab chiqarsa nimalar sodir bo'ladi? Ularni test qilish, ko'rikdan o'tkazish qiyinlashadi. Ko’p moshina chiqarish ko’p sotishga emas, ishlab chiqarishni butunlay to’xtashiga olib boradi. Qayta aytmoqchi bo'lgan so'zim, AI bilan kod yozish ishni tezlashtiradi, sifatni pasaytiradi. Kod yozish oldin ham muammo emas edi. Haqiqiy muammo kodni "r…
#experience Dropbox'da highly distributed systems qurganmiz deb ko'p aytganman. "O'zi tizimlarni nega distribute (tarqatish) qilish kerak?" degan savolga ham javob bermoqchiman. Ilgariroq agar dasturlar ko'proq foydalanuvchilarga xizmat ko'rsatishi kerak bo'lgan bo'lsa, insoniyat shunchaki serverlarga ko'proq va kuchliroq RAM, Disk va CPU qo'shib kuchaytirgan. Buni Vertical Scaling (chunki moshina eniga emas, bo'yi…
#experience Dropbox'da ishlab ko'p ajoyib narsalarga guvoh bo'lganman. Dunyo bo'ylab ko'p davlatlarda ish faoliyati yuritishiga qaramay, ishchilar soni unchalik ham ko'p bo'lmagan (muhandislar soni men kirganimda > 10k, va layoff'lardan keyin 4.9k qolgandi) kompaniya. Boshqa katta kompaniyalardan farqi bottom-up (basdan-yuqoriga) kulturasida ish yuritilardi, ya'ni muhandislar investorlarga nima ustida ishlashni ayti…
GridWall RL Environment Reinforcment Learning nimaligiga qiziqadiganlar uchun. Buni vizual ko'rish uchun ilgariroq bir o'yin yasagandim. Uni UI qismini AI dan yaxshilashini so'rab, sal to'g'irlab chiqardim. Kod imkon qadar oson yozilgan, iltimos qattiq kritika qilmang (yosh bo'lganmanda). GridWall o'yinini RL muhitda o'rganish jarayoni uchun o'yin. Siz uni o'rganish jarayonini kuzatib turolasiz. Juda oddiy va qiziq…
#startup Dropbox'da ML team kichik model train qilishgandi. Biz uni olib Reinforcement Learning muhitga tashlab uni qilayotgan ishlarini kuzatgandik. Bu joyiga to'liq to'xtala olmayman, ammo qiziq bir narsani aytmoqchiman. Agent muhitga tushganda turli xil yo'llarni sinab ko'radi. Agentga policy beriladi va u shundan chiqib ketmaslikga harakat qiladi. U har xil oldin ko'rmagan (pre-training jarayonida) ishlarni qil…
#startup Juda kuchli founder va oddiy founder lar o'rtasidagi eng katta farq matematikada ekan. Google TPU, Nvidia GPU, Intel CPU yaratayotgan jamolar bilan suhbat qildim. Xulosa bitta, ular matematikada kuchli. Misol uchun Dario Amodei (Anthropic), Ilya Sutskever (OpenAI), Sergey Brin (Google), Elon Musk (SpaceX, Tesla), Pavel Durov (Telegram), Jeff Bezos (Amazon), Mark Zuckerber (Meta), Vitalik Buterin (Ethereum)…
Bunday research talab qiladigan g'oyaga pul tikadigan investorlar juda kam, deyarli yo'q ayniqsa O'zbekistonda. Shuning uchun to'liq vaqtim va diqqatimni bu yerga qarata olmayabman. Ba'zi narsalar uchun pul kerak, pul topish uchun short-term ba'zi narsalarga rozi bo'lish kerak. Moshina yoqilg'isiz uzoqga borolmagani kabi, biz ham resurssiz (pul, vaqt va diqqatsiz) uzoqga borolmaymiz. Ammo umid qilamanki kelajakda bi…
Showing the 12 most recent of 20 posts we hold for @otabekswe. 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 — 196,599 of 1,160,990entries 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.
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 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.
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.
“Otabek’s I/O” (@otabekswe), 2,840 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/otabekswe.
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.