A hub for startup news, trends, and insights, covering the global startup ecosystem for founders, investors, and innovators.
Community: @startupdis
Buy Ads: @strategy (this is our only account).
Created
22 April 2019 — measured — dated from the channel’s first post
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 58% 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.
Observations
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
Content that also appears on other registered channels
Posts published here appear word for word on 2 other registered channels. They sit inside a group of 13 channels that share the same post bodies with each other. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.
Matching posts — open both and compare (6 of the pairs behind the counts below)
Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.
What this cannot establish
MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.
Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. None of the 7 matches recorded here fall after that date, so for this entry we cannot say whether any of them carried a credit. The duplication is measured; the absence of attribution is not.
“Published first” means first in this corpus. We hold 2,812 comparable posts for this entry, running 22 April 2019 to 7 August 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.
The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.
Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).
Across the whole group of 13, the earliest publisher we hold is @coinmarket. That is a statement about our reading window, not a claim of authorship.
Views and reactions moved apart
On 12 of the 78 posts we watched over 30 days, the view counter climbed while the reaction counter stayed where it was — by more than this channel’s own reactions-per-view rate can account for. That rate, measured on this entry, is 0.1822 reactions per view.
Each interval, as we read it — views and reactions before and after
Expected is the view gain multiplied by this channel’s own prior reactions-per-view rate over the same post — not a corpus average, so a channel whose audience never reacts is compared only against itself. Every interval is credited in the direction that makes the observation harder to record, never easier: t.me renders views and reactions to three significant figures above ~1,000, so a raw delta can be a rendering step. Every delta below is at least 4 x the coarser reading's step, the view gain is discounted by a full step and the reaction gain credited with one. Measured by tgregister velocity.py (our own t.me/s/ readings).
What this does and does not say. It says the two counters moved apart, by more than rounding and more than this channel’s own history predicts. It asserts no cause. Views arriving from outside Telegram, an embedded or forwarded copy of the post, and a burst of readers who simply do not react all produce this shape. This detector has recorded very few observations across the whole register, and its precision has not been measured; treat it as an anomaly worth looking at, not as a finding.
Recorded under the keys clone_copy · clone_source · view_reaction_decoupling, last confirmed 6 October 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
Also posting the same content
This channel’s posts match, word for word or near enough, posts on 12 other registered channels, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.
Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
85 measurements spanning 60 days, net -299,947. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 2,150,259–2,540,190 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 85
Measured (UTC)
Subscribers
Change
4 Oct 2026, 18:39
2,195,251
-580
4 Oct 2026, 14:37
2,195,831
-253
4 Oct 2026, 13:18
2,196,084
-38,459
26 Sept 2026, 21:40
2,234,543
-3,089
26 Sept 2026, 07:57
2,237,632
-511
26 Sept 2026, 05:01
2,238,143
-26,909
19 Sept 2026, 15:59
2,265,052
-441
19 Sept 2026, 10:20
2,265,493
-111
19 Sept 2026, 09:38
2,265,604
-11,503
17 Sept 2026, 07:00
2,277,107
-644
17 Sept 2026, 01:01
2,277,751
-438
16 Sept 2026, 20:00
2,278,189
-8,184
15 Sept 2026, 05:40
2,286,373
-1,528
15 Sept 2026, 00:39
2,287,901
-120
15 Sept 2026, 00:18
2,288,021
-6,719
13 Sept 2026, 15:19
2,294,740
-1,039
13 Sept 2026, 12:38
2,295,779
-263
13 Sept 2026, 11:21
2,296,042
-8,612
11 Sept 2026, 20:58
2,304,654
-1,022
11 Sept 2026, 16:21
2,305,676
first reading
Engagement
3,179 posts held, back to 22 April 2019 — the reader has reached the start of this channel’s public history, so this is the full archive Telegram still exposes. Read across 4,281 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
0.238%
avg views ÷ 2,195,251 subscribers
Avg views / post
5,220
93 posts measured
Reaction rate
19.1%
reactions ÷ views · ER floor
Posts in window
93
of 3,179 held
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.
What these figures were computed from
Window
Rolling 30 days · latest post in window 6 October 2026
Posts held
3,179 (22 April 2019 – 6 October 2026)
Views total
485,800
Reactions total
92,751
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
7 Oct 2026, 00:01 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.
What this channel posts
Photos
≈1,750
Videos
≈799
Links
≈1,910
Lifetime counters from Telegram’s own channel header, read 6 October 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.
Video runtime
1h 12m
Average length
52s
Measured directly from 84 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.
View velocity
How fast this channel’s own posts pick up views, from re-reading them repeatedly in the hours and days after they were published rather than the single reading most entries on this register get. Coverage is early and only a small minority of channels hold it at all — a gap in this section means the post has not been re-read again yet, not that nothing happened.
Computed from 78 of this channel’s own posts over the last 30 days (2 of the 24-hour readings behind this are interpolated, not measured directly): across 76 of this channel’s own posts with a clear reading, a typical one reaches half of its last-observed view count within 16 hours of being posted; a typical post has already reached 22.8% of its 24-hour view count within the first hour, and 60.6% within the first six; the median 24-hour reach across those posts is 3,180 views — 0.145% of this channel’s own subscriber count (90th percentile 3,475).
8 most recently posted, with a view-velocity reading
Curve is every standard checkpoint we hold a reading for (+1h, +3h, +6h, +12h, +24h, +48h, +7d after posting) — measured where a real reading landed close enough to that age, interpolated where it did not but readings on both sides let one be worked out between them. Nothing is ever extrapolated past the last real reading. Latest reading is the newest view and reaction count we hold for the post, side by side, so a gap between how views and reactions moved is visible without following it into the Observations section above. 24h reach is that one checkpoint on its own, labelled the same way. Half of last-observed views is the age at which a post’s view count crossed half of the highest figure we have read for it so far — an upper bound when the very first reading was already past half (we cannot see the actual crossing), and biased low while the post is still climbing, since “half of final” is dividing by a number that has not finished growing yet. Both caveats are printed inline wherever they apply, never silently dropped.
Reaction mix
188,840 reactions across 193 posts, in 19 distinct kinds. The most used accounts for 22.1% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
41,643
22.1%
👍
20,312
10.8%
👎
12,428
6.58%
🔥
12,184
6.45%
😁
11,316
5.99%
🤔
10,042
5.32%
😱
7,966
4.22%
👏
7,955
4.21%
🤯
7,691
4.07%
🙏
7,031
3.72%
🐳
6,499
3.44%
💯
6,450
3.42%
👌
6,390
3.38%
🤩
6,085
3.22%
🤝
5,980
3.17%
💔
5,760
3.05%
😢
4,653
2.46%
🎉
4,488
2.38%
🦄
3,967
2.10%
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 994 of the 1,000 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 449,601 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 1,000 most recent posts we hold (the sample is capped at 1,000), published 23 October 2025 to 6 October 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.
Telegram Stars
Stars received
10
across the posts below
Posts paid on
8
of 994 we hold a reading for · 0.8%
Most on one post
2
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @tech. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 1,000 most recent posts we hold for this entry (the sample is capped at 1,000), published 23 October 2025 to 6 October 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
🍏 Alyx Reaches Apple Vision Pro
The game runs natively, without a PC or streaming. The headset does all the rendering.
Valve ported Alyx to ARM64 for its Steam Frame headset, using a Qualcomm Snapdragon chip. An open project by ShinyQuagsire runs Android VR apps on Vision Pro. AI filled the compatibility gaps, followed by optimization.
On Vision Pro with the M5 chip, Alyx reaches about 3K per eye at 60 fps, with s…
🤖 GPT-6 Astra Played WoW Blind
With the monitor off, GPT-6 Astra completed the orc starting zone in about 40 minutes without processing rendered frames. It read the game through its network protocol via agent-wow.
A Python script converted message types into a live world view. Server SQL files exposed quest and NPC data, while Astra handled selling junk and upgrading gear. The author says it never died.
For moveme…
Ⓜ️ Meta Opens Muse to DIY Devices
Meta’s open-source platform connects the Muse AI agent to real hardware. Install the SDK on an ESP32, Raspberry Pi, or another Linux computer, then add compatible components. The SDK and firmware use the Apache 2.0 license.
That can produce a desktop AI assistant with a screen, a voice assistant, or a reminder display. Meta also showed Muse Home Link, a small USB device based on ES…
🤖 Anthropic Studies AI Morality
Since autumn 2025, Anthropic co-founder Chris Olah has held private talks with religious thinkers about AI consciousness and teaching models morality. Since March, he has led seminars for religious groups, with some participants signing NDAs.
Anthropic gave Claude an 84-page constitution describing its identity and values. Employees call it the “Soul Doc.” Olah says Claude shows inte…
🔍 Google puts 4 TPUs in orbit
Project Suncatcher launched on 1 October aboard a SpaceX rocket during Transporter-18. The satellite, built with Planet, carries 4 TPUs. Google confirmed contact and normal operation.
Over the next few weeks, the chips will be tested against radiation and temperature swings. The project studies whether AI computing can scale in orbit.
Solar panels in a suitable orbit can produce up to…
🤖 GPT-6.1 Astra May Arrive Next Week
Thibault and other OpenAI developers are hinting at the release.
GPT-6.1 Astra, or another strong model, was supposed to launch at DevDay but was postponed “for safety reasons.”
📊@tech
🙂↔️ DeepSeek Brings Harness to Desktop
Harness is available for macOS and Windows as an open-source alternative to Claude Code and Codex.
DeepSeek models act as autonomous agents. They write and test code, work with files and the terminal, then handle long tasks. Plugins allow customization.
📊@tech
🔗 AI Progress Could Compress Years
A Cambridge paper by 22 authors, including Geoffrey Hinton, Yoshua Bengio, OpenAI’s Jakub Pachocki, and Anthropic’s Jack Clark, examines compressing years of AI progress into months.
At Anthropic, model-written code rose from single digits to over 80% since early 2025. Autonomous R&D tasks rose from 1% to 26% in 6 months. Full automation could make progress 10x faster in about 1.5…
🤖 Karpathy Wants AI to Stop Writing Text
Karpathy suggests asking AI to explain complex topics in ASD-STE100 simplified English, with short sentences and little ambiguity. For harder subjects, a diagram or a custom HTML page can work better than plain text.
Modern models can already build one-off interfaces for a specific question. Karpathy is especially interested in personal teaching videos, with animation, a 3Bl…
🍏 Apple’s Camera Will Not Record Video
Apple is reportedly developing J450, a small cylindrical home security camera with a very low frame rate. AI analyzes what its sensor sees and produces only text descriptions, such as someone entering a room. Face recognition is also expected.
J450 is designed as a companion to Apple’s J490 smart home display. It is part of a broader smart home ecosystem that may include Apple…
🤖 ChatGPT Gets Virtual Try-On
OpenAI added virtual try-on to ChatGPT. When a clothing product card appears, tap “Try on” and upload a selfie plus a full-body photo. ChatGPT Images 2.5 generates the result.
The feature can also use clothing screenshots, not just items suggested by the bot. Favorite pieces can be saved to Library. Google added the same feature to Search in 2025.
The catch is privacy. By default, ima…
🍟 McDonald’s AI Suggests Local Big Mac Prices
In Fresno, a Big Mac costs $5.69 at one McDonald’s and $6.89 at another 2 miles away. That is a 21% gap, linked by Reuters to the chain’s AI pricing system.
The system seeks an “optimal price” for each US restaurant and some overseas markets, based on local customers’ willingness to pay. Franchisees see prompts about price sensitivity. McDonald’s tracks deviations and s…
🤯237❤225🙏214👍195👎135🔥112
Showing the 12 most recent of 3,179 posts we hold for @tech. 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.
Posts edited after publishing
@tech edited 1 post after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
First edit seen
9 August 2026
Most recent edit
9 August 2026
Mentions
Named by 17 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.
Handles this channel named that no longer answer
Dead references
8
handles named in this channel’s posts, vacant today
Evidenced gone
0
we ourselves saw one of these resolve, at some point
Never seen alive
8
vacant every time we have ever looked
@tech named 8 handles 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.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@pitchcamp named in 2 posts, 8 August 2026 – 8 August 2026
@collaboroovin named in 2 posts, 8 August 2026 – 8 August 2026
@globalpassinfo named in 1 post, 8 August 2026 – 8 August 2026
@heorhi_talochka named in 1 post, 8 August 2026 – 8 August 2026
@iamajeet2 named in 1 post, 8 August 2026 – 8 August 2026
@meta_orange named in 1 post, 8 August 2026 – 8 August 2026
@tedefibot named in 1 post, 8 August 2026 – 8 August 2026
@ether named in 1 post, 8 August 2026 – 8 August 2026
Channels Telegram recommends alongside this one
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 8 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.
Appears in Telegram’s recommendations for other channels
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.
Programmer ♨️ @programmer · 182,713 Telegram ranks this channel #1 of 78 here — alongside 77 others — read 11 August 2026
AI Post — Artificial Intelligence @aipost · 692,514 Telegram ranks this channel #1 of 83 here — alongside 82 others — read 8 August 2026
Venture Capital @venture · 2,159,722 Telegram ranks this channel #1 of 78 here — alongside 77 others — read 8 August 2026
Crypto Insider @coinmarket · 2,061,927 Telegram ranks this channel #1 of 79 here — alongside 78 others — read 8 August 2026
Trade Watcher @stockbot · 2,129,677 Telegram ranks this channel #2 of 79 here — alongside 78 others — read 8 August 2026
Not Memes @notmemes · 85,741 Telegram ranks this channel #4 of 81 here — alongside 80 others — read 18 August 2026
Solanapayouts.com @SolanaPayouts · 181,461 Telegram ranks this channel #5 of 79 here — alongside 78 others — read 11 August 2026
Everscale News @everscale_news · 275,219 Telegram ranks this channel #5 of 79 here — alongside 78 others — read 10 August 2026
The Daily Stats @dailystats · 30,591 Telegram ranks this channel #6 of 82 here — alongside 81 others — read 6 September 2026
KKX NEWS @kkxnews · 143,099 Telegram ranks this channel #8 of 78 here — alongside 77 others — read 12 August 2026
Newcastle United @newcastle · 94,398 Telegram ranks this channel #10 of 80 here — alongside 79 others — read 16 August 2026
$VODKA | MEMECOIN ON $SOL @vodkatokensol · 258,215 Telegram ranks this channel #14 of 80 here — alongside 79 others — read 10 August 2026
OOIA - TON NFT Marketplace @ooiaton · 264,753 Telegram ranks this channel #14 of 78 here — alongside 77 others — read 10 August 2026
TONX 💎 @TONXstudio · 102,887 Telegram ranks this channel #15 of 81 here — alongside 80 others — read 15 August 2026
Apple News @iphone · 141,973 Telegram ranks this channel #19 of 79 here — alongside 78 others — read 29 August 2026
tAppTales @tapptales · 102,037 Telegram ranks this channel #20 of 78 here — alongside 77 others — read 15 August 2026
BUSINESS TIPS 101 @bussiness101 · 37,497 Telegram ranks this channel #23 of 54 here — alongside 53 others — read 31 August 2026
Not Meme @notmeme · 160,137 Telegram ranks this channel #24 of 78 here — alongside 77 others — read 12 August 2026
ChatGPT Tips, Prompts & AI Tools @GPT_ChatGPT_AI_Tools · 60,205 Telegram ranks this channel #25 of 77 here — alongside 76 others — read 22 August 2026
🤖 Claude | GPT-6 | Deepseek | Gemini👨🏻💻 @gpt_anthropic · 24,897 Telegram ranks this channel #27 of 85 here — alongside 84 others — read 14 September 2026
CoLabs: coNFT, CoPump, CoPass @co_nft · 146,252 Telegram ranks this channel #28 of 81 here — alongside 80 others — read 12 August 2026
TON News @newston_en · 138,674 Telegram ranks this channel #29 of 78 here — alongside 77 others — read 13 August 2026
Tech, Science & Innovation @Tech_Science_Innovation · 37,737 Telegram ranks this channel #30 of 76 here — alongside 75 others — read 31 August 2026
Computer Science and Programming @computer_science_and_programming · 139,769 Telegram ranks this channel #30 of 87 here — alongside 86 others — read 13 August 2026
This channel appears in 50 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
Domains linked from posts
191 domains this channel’s own posts have linked to, measured by scanning the post bodies themselves — not the channel’s description, which is the separate Declared links section below when this entry has one. Appearing here is not a claim about who runs the linked site or why the channel linked to it; an advertisement, a news citation and a malicious link all leave the same kind of row.
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 4 October 2026 — this
entry's latest reading, not the date you are reading this.
“Startups & Ventures” (@tech), 2,195,251 subscribers as measured 4 October 2026. Telegram Register, tgregister.com/channel/tech.
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.
