የእግርኳስ ሆርሙዝ ሰርጥ 🔥
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Channel
@neural_netss
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Handles named that no longer answer · Cite this entry
2,241subscribers
-2 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
| Telegram ID | -1002226707118 |
|---|---|
| Type | Channel |
| Username | @neural_netss |
| Created | Between 1 June 2024 and 30 September 2024— 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/neural_netss |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 11 Aug 2026, 23:53 | 2,241 | -2 |
| 7 Aug 2026, 18:48 | 2,243 | no change |
| 7 Aug 2026, 17:42 | 2,243 | first reading |
16 posts held, back to 4 June 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 1 pageof 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 16 posts for this entry, the most recent from 17 June 2026. An engagement rate over an empty window would be a number about nothing.
Measured directly from 3 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.
195 reactions across 15 posts, in 13 distinct kinds. The most used accounts for 35.4% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 🔥 | 69 | 35.4% | |
| 😁 | 42 | 21.5% | |
| ❤ | 29 | 14.9% | |
| ⚡ | 20 | 10.3% | |
| 💔 | 17 | 8.72% | |
| 🤔 | 5 | 2.56% | |
| 🤣 | 3 | 1.54% | |
| 🤯 | 3 | 1.54% | |
| 🏆 | 2 | 1.03% | |
| 👏 | 2 | 1.03% | |
| 👌 | 1 | 0.513% | |
| 💯 | 1 | 0.513% | |
| 🙏 | 1 | 0.513% |
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 15 of the 16 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 195reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 16 most recent posts we hold, published 4 June 2026 to 17 June 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.
የእግርኳስ ሆርሙዝ ሰርጥ 🔥
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Introducing Papers API • scholarxiv.com/developers We hosted 3,032,697+ (3M+) papers so you don't have to explore research at the rate of one query per 3 seconds (arXiv's API limits) — instead you can explore research at 3,600 queries per hour. That's one query every single second, everyday! With that kind of rate you can imagine what kind of research agents and products you can build! Filter by title, author, cat…
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Today in ባህር ዳር
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Diogenes the Cynic's story is interesting. If I was a member of the parliament I'd have entered with lit lantern😂 https://penelope.uchicago.edu/encyclopaedia_romana/greece/hetairai/diogenes.html
so for world cup, I predicted 2/2 correct predictions 😎, I mean who is stopping me now. I dare you to ask me who the next PM of 🇪🇹 is going to be
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It's actually very fast, but not sure how much the throughput vs quality trade off is
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Diffusion Gemma is really nice. Making me go back to abandoned diffusion based text generation projects https://deepmind.google/models/gemma/diffusiongemma/
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New 4B translation model from Hasab AI for few Ethiopian langs. It's good to see almost everyone who is working on AI/ML in Ethiopia is releasing something. This will help a lot to make a progress. 👏 Hasab AI Now tag Ethiopian AI Institute to release something too 😁 https://huggingface.co/hasab-ai/YehaTranslate
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I'll share the results of my exploration this weekend. Hopefully a long report
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My weekly GPU usage📊 ~1267.2 kWh According to Gemini this can power an average household refrigerator for 14 to 16 months, or driving a standard electric vehicle (EV) for about 6,000 kms The good thing is the cluster runs on renewable energy so close to zero carbon footprint and recycles the heat back.
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Oh wow
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Saw a post about ScholarXIV from Babi, so you heard about fake citations right, well ScholarXIV can help with that🔥 But open research problem could be how can you ground the LLMs so they can cite exactly from the paper without altering results, no errors or attach the citation to the wrong sentence etc Maybe methods like on-policy distillation could help here, let a verifier identify where the model’s claim diverge…
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Showing the 12 most recent of 16 posts we hold for @neural_netss. 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.
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.
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.
@neural_netss named 1 handle that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all.A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
References a handle that is not a live channel — we have no record it ever was one.
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.
“Henok | Neural Nets” (@neural_netss), 2,241 subscribers as measured 11 August 2026. Telegram Register, tgregister.com/channel/neural_netss.
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.