Channel
@messelinks
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
24subscribers
+0 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1001908151467 |
|---|---|
| Type | Channel |
| Username | @messelinks |
| Description | Mostly links lost in saved messages on solutions engineering and simulation modelling topics at Deloitte-NVIDIA alliance. Named after the random station in Munich. |
| Created | Between 1 March 2023 and 30 November 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 11 August 2026 |
| Last confirmed live | 11 August 2026 |
| Measurements held | 2 |
| On Telegram | t.me/messelinks |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 11 Aug 2026, 11:04 | 24 | no change |
| 7 Aug 2026, 22:06 | 24 | first reading |
19 posts held, back to 26 March 2025 — 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 19 posts for this entry, the most recent from 12 June 2026. An engagement rate over an empty window would be a number about nothing.
Lifetime counters from Telegram’s own channel header, read 11 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
9 reactions across 6 posts, in 4 distinct kinds. The most used accounts for 66.7% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👀 | 6 | 66.7% | |
| ❤ | 1 | 11.1% | |
| 👍 | 1 | 11.1% | |
| 🤯 | 1 | 11.1% |
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 6 of the 19 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 9reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 19 most recent posts we hold, published 26 March 2025 to 12 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.
Technofeudalism Perhaps the best explanation of the future remaining before singularity/global war.. https://www.amazon.com/Technofeudalism-Killed-Capitalism-Yanis-Varoufakis/dp/1685891241
👍1
ICLR 20 best papers Article by Nebius Science listing 20 ICLR papers they considered important Nebius launched Science magazine recently to discuss relatively important research directions
❤1
Zero Trust in Agents ZT architecture of systems security which became standard for corporate systems is coming to be useful in agentic systems. The short video explaining the issue. The longer post with details. Nice field for research and testing.
👀1
Model Optimizer NVIDIA has a complete toolkit for optimising models. Includes PTQ, QAT and QAD Installs with pip install -U nvidia-modelopt[all] Examples here: https://github.com/NVIDIA/Model-Optimiser
Weight Transfers In a blogpost Plex research team tells how they risked implementing P2P RDMA tensor transfer from training to inference GPUs. it is needed for live updates on the production models when new data is added so it appears in the inference landscape asap. The conventional way is just bunch of RPC calls from training to inference with the ask to update weights. Normally requires a lot of additional stuff…
Infinite compute finetuning Stanford paper on what will happen if compute becomes nearly infinite with the data amount to train on stays constant. Quite slanted paper not considering many aspects like possible new architectures, continuous data representations, switch in hardware paradigm etc.
Mercedes GPUs Some rolling accelerators on SkyPilot. The platform is actually good anyways.
Clone Updates There’s now a little movie about the team and the first Protoclone
ZLUDA There's an initiative to create an open-source translation layer for CUDA. It means someone is writing custom everything to launch CUDA kernels, PyTorch, Llama.cpp etc. on non-NVIDIA hardware (AMD, Intel, Huawei, Biren etc.) Cool story with this former Intel&AMD polish guy in the main role, obvious pushback by Jensen and anonymous financial backer. Technically, it is possible but the complexity to make it, p…
4-bit pretraining This year, NV managed to improve MXFP4 format by involving some black magic on block sizes (by reducing the block size from 32 to 16 elements compared to MXFP4, NVFP4 minimizes the influence of outliers and enables more precise scaling). The format is called NVFP4 (literally NVIDIA floating point 4-bit). It has some more optimisations especially related to GEMM operations on Tensor cores (of cour…
👀2
NVIDIA Lepton One of the most controversial endeavors of NVIDIA management discussed more than a year ago also with Deloitte teams was Lepton Project. The idea is a meta-service covering all GPU providers managed directly by NVIDIA. Of course it all made a lot of indignation. This move even brought consensus between major hyperscalers (AWS, Microsoft) and smaller resource providers (Nebius, CoreWeave) to be upset w…
Docker Agents Docker Hub is preparing for the new MCP agent kung foo in the future. Here described how it'll look like. Promises to work with LangGraph, crew.ai (how tf they end up on crewai.com instead of crew.ai is a nonsense), Vercel, SpringAI and many others. "Now, with just a compose.yaml, you can define your open models, agents, and MCP-compatible tools, then spin up your full agentic stack with a simple doc…
Showing the 12 most recent of 19 posts we hold for @messelinks. 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 — 876,060 of 1,169,250entries 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 1 registered channel — 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.
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.
“messestadt” (@messelinks), 24 subscribers as measured 11 August 2026. Telegram Register, tgregister.com/channel/messelinks.
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.