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Telegram profile photo for Pictor | Official Channel

Channel

Pictor | Official Channel

@pictor_channel

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Handles named that no longer answer · Cite this entry

7,338subscribers

-290 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1002209379339
TypeChannel
Username@pictor_channel
CreatedBetween 1 June 2024 and 30 September 2024 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live18 September 2026
Measurements held15
Confirmed unchanged1 time, most recently 18 September 2026
On Telegramt.me/pictor_channel

Topic

Technology — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 12 September 2026 and assigned it the closest of 31 fixed categories, at 100% 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.

Growth

7,3387,6287,4837 August 2026 — 7,628 subscribers7 August 2026 — 7,628 subscribers8 August 2026 — 7,627 subscribers11 August 2026 — 7,617 subscribers14 August 2026 — 7,601 subscribers17 August 2026 — 7,586 subscribers20 August 2026 — 7,561 subscribers24 August 2026 — 7,551 subscribers26 August 2026 — 7,533 subscribers29 August 2026 — 7,519 subscribers2 September 2026 — 7,503 subscribers6 September 2026 — 7,483 subscribers11 September 2026 — 7,461 subscribers14 September 2026 — 7,448 subscribers18 September 2026 — 7,338 subscribers7 August 202618 September 2026
15 measurements spanning 42 days, net -290. 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 7,295–7,672 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
18 Sept 2026, 12:177,338-110
14 Sept 2026, 12:367,448-13
11 Sept 2026, 06:007,461-22
6 Sept 2026, 10:217,483-20
2 Sept 2026, 02:377,503-16
29 Aug 2026, 18:457,519-14
26 Aug 2026, 21:477,533-18
24 Aug 2026, 04:277,551-10
20 Aug 2026, 16:057,561-25
17 Aug 2026, 12:067,586-15
14 Aug 2026, 10:257,601-16
11 Aug 2026, 12:087,617-10
8 Aug 2026, 02:207,627-1
7 Aug 2026, 23:007,628no change
7 Aug 2026, 22:587,628first reading

Engagement

20 posts held, back to 27 January 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 15 pages of 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 20 posts for this entry, the most recent from 22 April 2026. An engagement rate over an empty window would be a number about nothing.

What this channel posts

Video runtime
4m 28s
Average length
45s

Measured directly from 6 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.

Reaction mix

107 reactions across 20 posts, in 1 kind.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
107100.0%

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 107 reactions 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 27 January 2026 to 22 April 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.

Recent posts

22 Apr 2026, 07:45 UTC314 views5 reactionsread 28 August 2026
Video

Why Can GPU-to-GPU Communication Outweigh Raw GPU Speed? When scaling AI systems, most teams default to adding more GPUs or upgrading to faster ones. But in workloads like distributed training, the real constraint often isn’t compute, it’s how GPUs talk to each other. As GPUs continuously exchange gradients, model states, and tensors, communication speed directly impacts: - Synchronization across GPUs - Training ef

5

15 Apr 2026, 10:48 UTC147 views5 reactionsread 28 August 2026
Photo

GPU Scheduling: Orchestrating Compute Across Teams at Scale As AI adoption grows, GPUs are no longer siloed within a single team. Today, multiple teams simultaneously run training, inference, and experiments, introducing a new layer of complexity: how to fairly and efficiently allocate compute resources. Without a robust scheduling system, issues quickly surface: - High-priority workloads get delayed due to lack of

5

10 Apr 2026, 08:06 UTC90 views1 reactionsread 28 August 2026
Video

From idea to AI product - now simpler than ever 🚀 This tutorial shows how to leverage GPU power on Pictor Network to deploy, experiment, and scale faster. With a flexible and cost-efficient infrastructure, it’s built for both solo builders and teams. Whether you're training models or building AI agents, the right compute makes all the difference. 👉 Get started: https://pictor.network Build faster. Scale smarter.

1

9 Apr 2026, 03:28 UTC128 views5 reactionsread 28 August 2026
Video

Pictor Network 🤝 InFlow Strategic Partnership Announcement We’re excited to team up with inflowpayai - the global payment service provider for agentic commerce to unlock the next frontier of AI commerce. This is where GPU infrastructure meets agentic payments, enabling AI agents to transact, execute, and scale autonomously, and how computing becomes programmable. Explore more 🧵 https://x.com/pictor_network/status/

5

6 Apr 2026, 07:05 UTC107 views5 reactionsread 28 August 2026
Photo

GPU Topology: The Hidden Driver of AI Training Performance When evaluating AI performance, most teams focus on GPU power and quantity. However, an often overlooked factor plays a crucial role in training efficiency: GPU topology - the way GPUs are interconnected and communicate within a system. For instance: - GPUs linked via NVLink enable ultra-fast data transfer - GPUs communicating through the CPU or PCIe introd

5

2 Apr 2026, 03:51 UTC103 views5 reactionsread 28 August 2026

AI is evolving fast, but what will actually power the next wave? -------- Quest: What will be the most critical resource for AI in Web3 in 2026? 🧠 A. Better AI models B. Scalable GPU infrastructure C. Decentralized data networks D. Autonomous AI agents Leave your thoughts below! https://x.com/pictor_network/status/2039550927225647303?s=20

5

24 Mar 2026, 10:33 UTC140 views5 reactionsread 28 August 2026
Photo

AI Agents Need More Than Intelligence 🧠 AI agents may be getting smarter, but they still rely on powerful computing behind the scenes. OpenClaw is helping define the next wave of AI: autonomous agents that can execute complex, multi-step workflows rather than simply responding to prompts. But no matter how advanced these agents become, they all depend on one essential layer: compute infrastructure. A typical OpenC

5

18 Mar 2026, 03:45 UTC125 views3 reactionsread 28 August 2026
Photo

🚀The 10 most popular AI apps globally till Mar. 2026🚀 AI has moved beyond hype & becomes an essential digital infrastructure. With more than 1.7 billion monthly users, competition is intensifying across established leaders and emerging innovators. With #ChatGPT at the front, alongside names like #Gemini, #Deepseek, and #Genius (Vietnam), the ecosystem is expanding rapidly and becoming increasingly competitive. 🌍 W

3

13 Mar 2026, 07:43 UTC131 views4 reactionsread 28 August 2026
Photo

🔗The Financial Pitfalls of Heavy GPU Investments🔗 Committing hundreds of thousands of dollars to GPU hardware can introduce significant financial risk. The expense goes far beyond purchasing high-end cards like NVIDIA H100 or NVIDIA A100. In reality, several hidden costs and operational risks quickly add up, including: - The infrastructure required to run them: servers, electricity, and cooling systems - Fast hardwa

4

3 Mar 2026, 10:40 UTC116 views7 reactionsread 28 August 2026
Video

AI Agents: Building the Enterprise Virtual Workforce In 2026, the question is how far AI Agents can scale productivity. AI Agents are more than chatbots. They reason, use tools, run multi-step workflows, and operate 24/7, supporting data analysis, content creation, software operations, and customer service at scale. They’re becoming a true virtual workforce layer inside modern organizations. But scale demands infr

7

26 Feb 2026, 04:16 UTC107 views4 reactionsread 28 August 2026
Photo

🚀 WINNERS ANNOUNCEMENT 🚀 A big congratulations to all the champions of the Pictor Art Challenge and a heartfelt thank you to everyone who participated and shared your creativity with us! Check out the full list of winners here: https://docs.google.com/spreadsheets/d/1wtfpXADjmM1fshcu11m6OUDClDe1ZBTNaEBtOOBHzbs/edit?gid=0#gid=0 🌟 Next: Winners, kindly comment your BEP20 wallet address within 24 hours via this post

4

24 Feb 2026, 03:53 UTC93 views9 reactionsread 28 August 2026
Photo

GPU Fragmentation: The Silent Cost Multiplier in AI Infrastructure When talking about rising GPU bills, the team often blames shortages, demand, or scale, but the real issue is usually hidden within your own infrastructure. GPU fragmentation occurs when compute and VRAM are technically available but cannot be effectively utilized because workloads are poorly matched, rigidly allocated, or inefficiently scheduled.

9

Showing the 12 most recent of 20 posts we hold for @pictor_channel. 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.

Mentions

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.

Cite this entry

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 18 September 2026 — this entry's latest reading, not the date you are reading this.

“Pictor | Official Channel” (@pictor_channel), 7,338 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/pictor_channel.

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.