#lrms

Live, measured metrics for the hashtag #lrms from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.

hashtag.org network · sponsored

Own #lrms

This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.

$2,449.80/ year · 4-character #name
Claim #lrms — $2,449.80/yr→Buy on hashtag.space (web3)
card via hashtag.org · tokens via hashtag.space
0
Uses / 7 days
Mastodon
0
Accounts / 7 days
Mastodon
15
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 15
0.1
Avg reactions / post
Mastodon · last 15
—
Reddit posts / month
Reddit search
—
Open-web mentions
hashtag.org Firehose

Day-by-day usage

measured · mastodon.social (Mastodon public tags API) · fetched 2026-10-20 21:11 UTC
0
10-14
0
10-15
0
10-16
0
10-17
0
10-18
0
10-19
0
10-20

0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.

Related hashtags

measured · mastodon.social (Mastodon public search API) · fetched 2026-10-20 21:11 UTC

No related tags with measured usage found for #lrms.

Live pulse

measured · mastodon.social (Mastodon tag timeline) · fetched 2026-10-20 21:11 UTC

Everything below is measured over the latest 15 public posts (spanning ~16219 hours).

Posting hours (UTC) — busiest: 17:00

00:0012:0023:00

Languages: English (14) · Portuguese (1)

Avg boosts / post: 0.3

Top of the latest posts

  • I’ve been wondering what the “thoughts” really mean for an LLM: “Is AI Reasoning Right For The Wrong Reasons?”, Quanta (https://www.quantamagazine.org/is-ai-reasoning-right-for-the-wrong-reasons-20260731/). Via HN: https://news.ycombinator.

    रञ्जित (Ranjit Mathew)@rmathew♥ 1↻ 02026-08-02 13:30 UTCView post →

  • Ah yeah, OpenAI claims again it solved an Erdos problem. What they are not telling is they did already claim they solved a bunch of these before... but they didn't, their LRM just found solutions that already existed in the literature. #LLM

    doragasu@doragasu@mastodon.sdf.org♥ 0↻ 02026-05-21 15:52 UTCView post →

  • “ #neuralnetworks of various kinds can generalise within a distribution of #data they are exposed to, but their generalisations tend to break down beyond that distribution.” www.theguardian.com/commentisfre... #AI #AGI #LLMs #LRMs When bill

    Don “Dr Mabuse” Curren 🇨🇦🇺🇦@dbcurren.bsky.social@bsky.brid.gy♥ 0↻ 12025-08-20 11:43 UTCView post →

#lrms across platforms

every network with a public tag surface

Follow #lrms straight to each platform’s own tag page. Where a platform publishes open data we measure it above; the rest lock their numbers behind paid APIs, so we link rather than guess.

X (Twitter) ↗Instagram ↗TikTok ↗Facebook ↗LinkedIn ↗YouTube ↗Threads ↗Bluesky ↗Mastodon ↗Reddit ↗Pinterest ↗Tumblr ↗

Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/lrms