#lossy
Live, measured metrics for the hashtag #lossy from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #lossy
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 · mas.to (Mastodon public tags API) · fetched 2026-10-23 19:40 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · mas.to (Mastodon public search API) · fetched 2026-10-23 19:40 UTCLive pulse
measured · mas.to (Mastodon tag timeline) · fetched 2026-10-23 19:40 UTCEverything below is measured over the latest 14 public posts (spanning ~48099 hours).
Posting hours (UTC) — busiest: 11:00
Languages: English (12) · Spanish (1)
Avg boosts / post: 0.4
Top of the latest posts
Lossless converting the paletted PNG (at 100671 bytes ≈ 101 kB) to JPEG XL result in a file at 25178 bytes ≈ 25 kB. Converting lossless to webp, using cwebp -lossless -m 6 -z 9 -o e08463_353cfb9f6bf646159fdf9dc573b1080e.{webp,png} the file
New #blog #post: Gratitude Day 14: Apple Video Codec https://rldane.space/gratitude-day-14-apple-video-codec.html 524 words cc: my wonderful #chorus: @joel @dm @sotolf @thedoctor @pixx @orbitalmartian @adamsdesk @krafter @roguefoam @clayton
R.L. Dane :Debian: :FreeBSD: :OpenBSD: :NetBSD:🍵 :MiraLovesYou:@[email protected]♥ 0↻ 02026-09-14 13:46 UTCView post →Exploring Hidden JPEG Features https://fed.brid.gy/r/https://hackaday.com/2026/07/24/exploring-hidden-jpeg-features/
What “lossy” means
WikipediaIn information technology, lossy compression, or irreversible compression, is the class of data compression methods that uses inexact approximations and partial data discarding to represent the content. These techniques are used to reduce data size for storing, handling, and transmitting content. Higher degrees of approximation create coarser images as more details are removed. This is opposed to lossless data compression which does not degrade the data. The amount of data reduction possible usi
“Lossy compression” on Wikipedia (CC BY-SA) →#lossy across platforms
every network with a public tag surfaceFollow #lossy 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.
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/lossy