#languageModels
Live, measured metrics for the hashtag #languageModels from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #languagemodels
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.
Day-by-day usage
measured · mastodon.online (Mastodon public tags API) · fetched 2026-07-27 02:20 UTC10 uses by 3 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · mastodon.online (Mastodon public search API) · fetched 2026-07-27 02:20 UTCLive pulse
measured · mastodon.online (Mastodon tag timeline) · fetched 2026-07-27 02:20 UTCEverything below is measured over the latest 40 public posts (spanning ~1880 hours).
Posting hours (UTC) — busiest: 06:00
Languages: English (24) · Polish (16)
Avg boosts / post: 0.7
Top of the latest posts
English language as a poor choice for training language models [*you don't say!*]. David Eichler proposes Basque, a language with very explicit consistency rules in its sentence structure that double as constraints for correctness. "The hyp
AI Coding Agents Exposed to Predictable Name Attacks Researchers have made a startling discovery: AI coding agents are surprisingly predictable, often generating identical fake names for tasks like skill installs and repository requests, ma
How a computer reads text - from counting words to vectors From tokenization through TF-IDF and Markov chains, to Word2Vec. How a computer turns text into numb... https://gruszka.dev/en/how-computer-reads-text.html #llm #ai #nlp #tokenizati
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/languagemodels