#textembeddings
Live, measured metrics for the hashtag #textembeddings from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #textembeddings
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 · fosstodon.org (Mastodon public tags API) · fetched 2026-07-27 06:58 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · fosstodon.org (Mastodon public search API) · fetched 2026-07-27 06:58 UTCLive pulse
measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-27 06:58 UTCEverything below is measured over the latest 4 public posts (spanning ~2064 hours).
Posting hours (UTC)
Languages: English (4)
Avg boosts / post: 0
Top of the latest posts
🚨BREAKING NEWS🚨: Shocking revelation: all text embeddings are just clones of each other! 🤖 Meanwhile, arXiv's desperate plea for a #DevOps engineer means that even universal geometry can't fix this cosmic mess. 🛠️🙄 https://arxiv.org/ab
All Text Embeddings Learn the Same Thing https://arxiv.org/abs/2505.12540 #HackerNews #TextEmbeddings #NLP #MachineLearning #Research #AIInsights #Arxiv
Embedding Models Misunderstand Language: ➡️ Text embeddings have blind spots, like capitalization misunderstandings, numerical inaccuracies, inability to detect negations, and confusion with ranges. ➡️Industry stories show dramatic conseque
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/textembeddings