در مورد استاندارد OKF از Google به این پست اضافه کنم که: ۱- این کار گوگل از LLM Wiki آندره کارپاثی الهام گرفته شده ۲_ یک از دو فرد اصلی این پروژه آقای امیر حرمتی هستن که در این مورد مصاحبه فارسی هم داشته: YouTube link
👍9❤3

Channel
@deeptimeai
On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry
3,765subscribers
+9 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
| Telegram ID | -1001527188232 |
|---|---|
| Type | Channel |
| Username | @deeptimeai |
| Created | Between 1 August 2021 and 31 January 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 11 August 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 1 time, most recently 11 August 2026 |
| On Telegram | t.me/deeptimeai |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 11 Aug 2026, 03:21 | 3,765 | +6 |
| 7 Aug 2026, 23:02 | 3,759 | +3 |
| 7 Aug 2026, 06:15 | 3,756 | first reading |
20 posts held, back to 22 October 2025 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 4 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 (22 October 2025 – 26 July 2026) |
| Views total | 2,890 |
| Reactions total | 51 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 8 Aug 2026, 06:14 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.
519 reactions across 20 posts, in 9 distinct kinds. The most used accounts for 55.1% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 286 | 55.1% | |
| 👍 | 210 | 40.5% | |
| 🔥 | 10 | 1.93% | |
| 💯 | 6 | 1.16% | |
| ✍ | 2 | 0.385% | |
| 👾 | 2 | 0.385% | |
| 🆒 | 1 | 0.193% | |
| 👌 | 1 | 0.193% | |
| 🤩 | 1 | 0.193% |
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 20 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 519reactions 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 22 October 2025 to 26 July 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.
در مورد استاندارد OKF از Google به این پست اضافه کنم که: ۱- این کار گوگل از LLM Wiki آندره کارپاثی الهام گرفته شده ۲_ یک از دو فرد اصلی این پروژه آقای امیر حرمتی هستن که در این مورد مصاحبه فارسی هم داشته: YouTube link
👍9❤3
این آهنگ برای کساییه که توی این دنیای پر از ادعا، بیادعا ترین قشر بودن... به سلامتیِ سربازهای وظیفهای که هیچوقت، هیچکس قدرشون رو ندونست🪖🥀 🆔 @radiometal_channel
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مدت زیادی باور بر این بود که به طور کلی Claude در نوشتن کد حرف اول رو میزنه. اما اخیرا که مدلهای جدید OpenAI معرفی شدن در یکسری کار پیچیده Quantitative Finance که برای سنجش مدلها استفاده میکنیم، مدل Sol بسیار بهتر از مدلهای Claude عمل کرد. مصرف توکن بهتری هم داشت. مدل جدید Grok 4.5 هم در مصرف توکن و به نسبت دقتی که داره واقعا بی نظیر هست. البته همه این موارد طبق مشاهدات محدود هست. رقابت بین شرکتها همیشه به نفع…
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حدودا بلافاصله بعد از قرارداد همکاری که با یک گروه معاملهگر داشتیم، به نوعی خواستن نشون بدن که استراتژی قدرتمندی دارن و به شکل هیجانی با مشاورهای که از تیم نرمافزاری خودشون گرفته بودن، طبق سیگنال سیستمشون معاملات پلهای باز کردن و در چند دقیقه چند هزار دلار باختن. این نوع معاملات شاید بدون حضور نرمافزار زیاد باشه اما وقتی افرادی میان و استراتژی رو به هر نحوی بکتست میگیرن باید یک اصل نانوشته رو بدونن: هدف از بکت…
👍12❤5
درباره الگوریتمیک کردن استراتژیهای معاملاتی تریدر های حرفهای زیادی در کانال هستن که مدتهاست (به طور دستی یا نیمه اتومات) فعالیت دارن. اما اکثرا تجربه خوبی از اتومات کردن، پیادهسازی نرمافزاری یا بکتست ندارن. علت: اکثر تیمهای نرمافزاری که تریدرها یا اساتید مدرس و ... باهاشون کار میکنن، حتی اگر کار درست باشن، کوئانت ندارن یا اگر دارن فقط اسمش هست! مسائل کوئانت فایننس به طور خاص نیازمند domain expertise و تجربه …
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معرفی KVarN گوگل چند وقت پیش یک روش بهینه در مدیریت KV cache به نام TurboQuant معرفی کرد که اساسا خود KV Cache رو کوئانتایز میکرد و بعد برای پروسه attention مجدد تبدیل به دقت بالاتر. اما vLLM با بنچمارک نشون داد که این کم شدن Memory Usage یا افزایش ظرفیت به قیمت از دست رفتن Accuracy و کم شدن throughput هست. این کاهش دقت خصوصا در long-cotext بیشتر دیده میشه چراکه error ها با این تبدیل به مرور زیاد میشن. حالا Huawei…
👍10❤7🔥1
هوش مصنوعی و خصوصا LLM ها دنیای بازارهای مالی رو متحول کردن (واضحا!). به همین دلیل در مورد LLM ها بیشتر پستهای تکنیکال میذارم. در سطح Trade: اگر به عنوان یک کوئانت فقط روشهای کلاسیک آماری/ دیتاساینس و مهندسی داده بلد باشید از رقابت کنار میرید. برای مثال بغیر از استفاده بهینه از مدلها برای کدنوشتن و ... باید بتونید روشهای LLM Inference سریع و در عین حال دقیق رو مسلط باشید و چند ثانیه/ میلی ثانیه در پردازش اطلاعا…
❤12👍4
یک مسئله جالب که این روزها بهش فکر میکنم تایید کورکورانه دوطرفه در تعاملات انسان با AI هست. تایید کورکورانه از جانب انسان: اینکه اگر شخصی فقط خروجیهای هر مرحله از AI رو بدون بررسی تخصصی تایید کنه، دو مشکل خواهد داشت: ۱_ احتمال کیفیت پایین خروجی یا بهینه نبودن ۲_ خودِ این شخص به راحتی با AI جایگزین خواهد شد چون در مجموع ارزشی اضافه نخواهد کرد پس اگر از آندره کارپاثی میشنوید که دیگه خودش تقریبا کدی نمینویسه به این م…
❤17👍11🔥1
Brain Foundation Model انگار داره کلاه سرمون میره Sabi.com این واقعا میتونه game changer باشه در دنیا. قطعا زندگی معلولین در آینده متفاوت میشه اما آیا این تنها استفاده هست؟! دریافت سیگنالهای مغزی به شکل wireless از طریق یک کلاه و تبدیل فکر به متن و بعدش هم که مشخصه: متن به AI برای انجام کار اما بازم میگم، تتها استفاده این موارد تبلیغی نخواهد بود. فکر کنید به روزی که کارمند ها مجبور به استفاده از این مورد بشن. هم…
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کنفرانس NeurIPS 2025 یک بخش ویژه فایننس داره که میتونید ببینید: NeurIPS 2025 Workshop on Generative AI in Finance اولین سخنرانی که معرفی شده آقای Rama Cont استاد ریاضی فایننس و هوش مصنوعی فایننس از دانشگاه Oxford هست. نکته مهم اینکه ایشون ایرانی هستن و اتفاقا بسیار عرق ملی دارن. من از طریقی ایشون رو میشناسم و شاید فرصت شد یکبار در کانال بیان صحبت کنیم.
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طبیعی هست که NVIDIA بی کار نخواهد نشست ایده اساسی CUDA Tile تمرکز روی الگوریتم بجای درگیر شدن با پیچیدگیهای سختافزار در GPU Programming هست. برای کار در پایتون: NVIDIA CUDA Tile in Python
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در ادامهی پستهای کانال، قصد داریم کتاب Build A Robo-Advisor with Python: Automate Your Financial and Investment Decisions را همراه با هم بخوانیم و بررسی کنیم. این کتاب توسط انتشارات Manning منتشر شده و تمرکز آن بر شیوههای مدیریت سرمایهگذاری مالی است. نگاه کتاب به سرمایهگذاری بلندمدت است و وارد مباحث مربوط به ترید نمیشود. نویسندگان تلاش کردهاند به پرسشهای زیر پاسخ دهند: ۱. چطور یک سبد سرمایهگذاری مناسب تش…
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Showing the 12 most recent of 20 posts we hold for @deeptimeai. 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 — 831,398 of 1,169,250entries 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 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 11 August 2026 — this entry's latest reading, not the date you are reading this.
“Deep Time” (@deeptimeai), 3,765 subscribers as measured 11 August 2026. Telegram Register, tgregister.com/channel/deeptimeai.
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.