Proof of Work. Proof of the CLEAN. Proof the next cycle starts with better inputs.
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Channel
@port3network
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry
40,722subscribers
-1,106 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
| Telegram ID | -1001279689024 |
|---|---|
| Type | Channel |
| Username | @port3network |
| Description | Website > https://www.port3.io TG Global Chat > https://t.me/port3network Socials > https://bento.me/port3network ~ Incentivizing Intelligence in Trustless Networks |
| Created | Between 1 April 2018 and 31 July 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 5 September 2026 |
| Measurements held | 29 |
| Confirmed unchanged | 1 time, most recently 5 September 2026 |
| On Telegram | t.me/port3network |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 5 Sept 2026, 15:56 | 40,722 | -80 |
| 3 Sept 2026, 19:55 | 40,802 | -42 |
| 2 Sept 2026, 08:44 | 40,844 | -68 |
| 1 Sept 2026, 05:45 | 40,912 | -41 |
| 31 Aug 2026, 07:04 | 40,953 | -50 |
| 30 Aug 2026, 05:54 | 41,003 | -45 |
| 29 Aug 2026, 05:34 | 41,048 | -36 |
| 28 Aug 2026, 01:58 | 41,084 | -26 |
| 27 Aug 2026, 00:33 | 41,110 | -32 |
| 25 Aug 2026, 22:03 | 41,142 | -29 |
| 24 Aug 2026, 20:57 | 41,171 | -72 |
| 23 Aug 2026, 08:14 | 41,243 | -39 |
| 21 Aug 2026, 18:08 | 41,282 | -31 |
| 20 Aug 2026, 17:43 | 41,313 | -36 |
| 19 Aug 2026, 18:28 | 41,349 | -33 |
| 18 Aug 2026, 15:56 | 41,382 | -35 |
| 17 Aug 2026, 19:16 | 41,417 | -26 |
| 16 Aug 2026, 15:19 | 41,443 | -51 |
| 14 Aug 2026, 20:56 | 41,494 | -55 |
| 13 Aug 2026, 13:05 | 41,549 | first reading |
24 posts held, back to 7 April 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 66 pages of 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 27 August 2026 |
|---|---|
| Posts held | 24 (7 April 2026 – 27 August 2026) |
| Views total | 3,262 |
| Reactions total | 43 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 7 Sept 2026, 11:47 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 7 September 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.
Measured directly from 2 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.
470 reactions across 23 posts, in 7 distinct kinds. The most used accounts for 34.5% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 🔥 | 162 | 34.5% | |
| 👍 | 86 | 18.3% | |
| ❤ | 66 | 14.0% | |
| 👏 | 61 | 13.0% | |
| 🎉 | 59 | 12.6% | |
| 💯 | 35 | 7.45% | |
| 👌 | 1 | 0.213% |
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 24 of the 24 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 489 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 24 most recent posts we hold, published 7 April 2026 to 27 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.
Proof of Work. Proof of the CLEAN. Proof the next cycle starts with better inputs.
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Choose your signal. Choose your edge. Choose the layer that turns chaos into clarity.
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GM. Time to stop scrolling noise. Start feeding the Agents that actually move.
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One dataset, one agent, and a better future.
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Black-box datasets are becoming a liability. As AI moves into enterprise and regulated industries, transparent data pipelines, auditable labeling, and verifiable provenance are no longer nice-to-have. They’ll be the new baseline.
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The AI data playbook is changing. More teams are focusing on three things. ✓ Synthetic data to scale. ✓ Quality control to reduce noise. ✓ Agent feedback loops to improve every round. The next breakthrough won’t come from more data. It will come from better data.
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AI models are engines. Data is fuel. And raw fuel doesn’t take you very far. The future belongs to those refining data before everyone else.
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A lot of attention is going to AI governance right now. Some believe governments should have a larger role. Others think private companies should lead. We have a different question. Should the people generating the data have more ownership in the AI systems built from it? Curious to hear your thoughts.
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The internet gave AI access to information. The next challenge is finding information worth learning from. The gold rush has already started.
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Raw Data → Filter → Clean → Structure → Ready to Use The value isn’t in collecting more data. It’s in making data useful.
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AI Agents are getting smarter every month. But there is one problem that keeps showing up again and again — Bad data. Most Web3 data is still fragmented across chains, protocols, and platforms. Port3 turns that complexity into structured, real time information that Agents can actually use. Because better outputs start with better inputs. Explore the Port3 Data Layer https://port3.io
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The biggest unlock for AI right now is not more models but better data foundations. Messy inputs hold everything back. We are fixing it with verified structured sources that let agents reason clearly. This image captures the vision perfectly.
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Showing the 12 most recent of 24 posts we hold for @port3network. 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.
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 6 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 29 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 2 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 5 September 2026 — this entry's latest reading, not the date you are reading this.
“Port3 Announcement” (@port3network), 40,722 subscribers as measured 5 September 2026. Telegram Register, tgregister.com/channel/port3network.
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.