Channel
@solidusaitech
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry
182,135subscribers
-981 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 100,000–316,228.
| Telegram ID | -1001592181626 |
|---|---|
| Type | Channel |
| Username | @solidusaitech |
| Description | Enterprise-grade AI infrastructure ecosystem enabling autonomous AI systems at scale. |
| 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 | 12 August 2026 |
| Measurements held | 7 |
| Confirmed unchanged | 1 time, most recently 12 August 2026 |
| On Telegram | t.me/solidusaitech |
Technology — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 8 August 2026 and assigned it the closest of 31 fixed categories, at 99% 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 12 Aug 2026, 17:06 | 182,135 | -166 |
| 11 Aug 2026, 18:46 | 182,301 | -159 |
| 10 Aug 2026, 21:07 | 182,460 | -140 |
| 10 Aug 2026, 00:30 | 182,600 | -173 |
| 9 Aug 2026, 00:55 | 182,773 | -174 |
| 7 Aug 2026, 23:53 | 182,947 | -169 |
| 7 Aug 2026, 00:47 | 183,116 | first reading |
36 posts held, back to 30 July 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 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 12 August 2026 |
|---|---|
| Posts held | 36 (30 July 2026 – 12 August 2026) |
| Views total | 457,831 |
| Reactions total | 726 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 12 Aug 2026, 18:02 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.
Lifetime counters from Telegram’s own channel header, read 12 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
726 reactions across 36 posts, in 12 distinct kinds. The most used accounts for 43.8% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 🔥 | 318 | 43.8% | |
| ❤ | 87 | 12.0% | |
| ✍ | 82 | 11.3% | |
| 👍 | 63 | 8.68% | |
| 🏆 | 57 | 7.85% | |
| 🥰 | 56 | 7.71% | |
| ⚡ | 37 | 5.10% | |
| 💯 | 14 | 1.93% | |
| ❤🔥 | 7 | 0.964% | |
| 👌 | 2 | 0.275% | |
| 😱 | 2 | 0.275% | |
| 🎉 | 1 | 0.138% |
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 36 of the 36 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 726reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 36 most recent posts we hold, published 30 July 2026 to 12 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.
Procurement is now part of the roadmap. AI used to get built first and approved later. A team would prototype something, prove it worked, then loop in procurement once it needed a real budget. That order is reversing. Security questionnaires, data handling reviews, and vendor risk assessments now shape which tools even make it to the prototype stage. Procurement isn't the final gate before launch anymore. It's a d…
👍5🥰2✍1
Batch jobs and real-time jobs need different infrastructure. Training a model overnight and serving live inference to users are not the same workload, even if they run on similar hardware. One tolerates delay. The other can't survive it. Running both on the same setup usually means one of them is quietly underperforming, and it's rarely the batch job that suffers. Matching infrastructure to workload type isn't op…
👍14
Spot pricing for compute: who actually benefits? Spot pricing looks like a discount. It's really a trade-off. Lower cost in exchange for the possibility that the resource gets reclaimed mid-job. That trade works well for flexible, interruptible workloads. It works badly for anything time-sensitive or customer-facing. The teams who benefit most aren't the ones chasing the lowest price. They're the ones who know ex…
🔥14❤3👍2😱1
Strategic Partnership: AITECH Cloud Network x Secret Network! We're excited to share a new partnership between AITECH Cloud Network and Secret Network, focused on bringing confidential computing to Agent Forge and reinforcing enterprise-grade privacy across the AI and Web3 landscape. Secret Network's confidential computing infrastructure will be integrated into Agent Forge, enabling users to build and deploy AI age…
✍22👍11❤4❤🔥3🏆1🥰1
What slows your AI projects down the most? 👉 Answer here: https://x.com/AITECHio/status/2087150179627811151?s=20
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An agent's audit trail matters more than its output. When an agent takes an action, the result is only half the story. What matters just as much is whether there's a record of why it did what it did, what data it used, and what it was allowed to touch. An agent nobody can audit isn't autonomous. It's a black box that happens to be useful, until it isn't.
🔥16🏆3🥰1
Weekly Development Update! Development continues across the Compute Marketplace and Agent Forge, with ongoing progress focused on performance optimization, staking infrastructure, and platform stability. Compute Marketplace • Optimized platform performance by fixing a memory bloat issue. • Set up endpoints for the CDC staking mechanism. • Finalizing additional regional vendors. Agent Forge • Set up endpoints for…
🔥17❤7🥰2🏆1
The real bottleneck is data transfer, not GPUs. Most conversations about compute scarcity stop at GPU availability. But a GPU sitting idle while data moves in and out is still a GPU you're paying for and not using. Bandwidth between storage and compute, not raw processing power, is often what actually caps throughput. More GPUs won't fix a pipe that's too narrow to feed them.
🔥16🥰2❤1🏆1💯1
Bigger models aren't always the right tool for the job. It's easy to assume the largest available model is the safest choice. But a smaller, specialized model often performs just as well on a narrow task, at a fraction of the compute cost and latency. The biggest model isn't a default. It's a tradeoff, and not always the right one.
🔥15⚡3🏆1
🗞 ACN Weekly Snapshot! Hey everyone, here's your ACN Weekly Snapshot, let’s dive in! ➡️ Read here: https://x.com/aitechio/status/2086483463126020578?s=46
⚡6🏆1
The best agents fail quietly, not loudly. A badly designed agent fails in ways everyone notices: a wrong answer, a broken output. A well-designed agent fails safely: it flags uncertainty, stops before taking a risky action, and asks for input instead of guessing. The goal isn't an agent that never fails. It fails in a way nobody has to clean up after.
✍16👍5🏆1
🗞️ AI News Roundup! Welcome to this week’s AI News Roundup, let’s dive into the seven headlines that had everyone talking! ➡️ Read here: https://x.com/aitechio/status/2086122477873230245?s=46
❤7🏆6
Showing the 12 most recent of 36 posts we hold for @solidusaitech. 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 — 428,261 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.
Named by 5 registered channels — 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.
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.
Telegram’s own answer, not this register’s.When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Read from Telegram’s recommendation API, most recently 12 August 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
This channel appears in 9 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 12 August 2026 — this entry's latest reading, not the date you are reading this.
“ACN ANNOUNCEMENTS” (@solidusaitech), 182,135 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/solidusaitech.
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.