#trainingdata

Live, measured metrics for the hashtag #trainingdata 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 #trainingdata

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.

$5.00/ year · 12-character #name
Claim #trainingdata — $5.00/yr→Buy on hashtag.space (web3)
card via hashtag.org · tokens via hashtag.space
1
Uses / 7 days
Mastodon
1
Accounts / 7 days
Mastodon
40
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 40
0
Avg reactions / post
Mastodon · last 40
—
Reddit posts / month
Reddit search
—
Open-web mentions
hashtag.org Firehose

Day-by-day usage

measured · mastodon.online (Mastodon public tags API) · fetched 2026-10-29 01:08 UTC
0
10-23
0
10-24
1
10-25
0
10-26
0
10-27
0
10-28
0
10-29

1 uses by 1 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 2026-10-29 01:08 UTC

Live pulse

measured · mastodon.online (Mastodon tag timeline) · fetched 2026-10-29 01:08 UTC

Everything below is measured over the latest 40 public posts (spanning ~2489 hours).

Posting hours (UTC) — busiest: 05:00

00:0012:0023:00

Languages: English (39) · German (1)

Avg boosts / post: 4.4

Top of the latest posts

  • 0xMarioNawfal - The Roundtable Show (@RoundtableSpace) NVIDIA가 로봇 학습용 영상 라벨링을 위한 오픈 모델 Flora를 공개했다. 영상 1시간당 약 0.72달러의 비용을 목표로 하며, NVIDIA 추산으로는 GPT-6 Astra 대비 약 125배 저렴하다. 단, 비교 비용은 실제 청구액이 아닌 추정치다. 로봇 데이터셋 구축·라벨링 파이프라인의 비용 절감 가능성을 시사한다. htt

    ainews@[email protected]♥ 0↻ 02026-10-25 22:50 UTCView post →
  • Varun Nair (@_varunnair) NVIDIA가 학습 데이터에 풍부한 신호를 추가하는 어노테이션 모델 제품군을 공개했다는 소식이다. 데이터 기업과 ML 팀은 자동 라벨링·메타데이터 보강을 통해 데이터 품질 기준을 높이고, 모델 학습용 데이터셋 구축 비용과 시간을 줄일 수 있는 방향이다. https://x.com/_varunnair/status/2112603276546032096 #nvidia #dataannotati

    ainews@[email protected]♥ 0↻ 02026-10-20 20:57 UTCView post →
  • Yusuf Ahmed (@yusufksadek) DeepSeek-R1 추론 트레이스 기반 증류 데이터셋에서 약 1.2만 개 문제 중 약 9%가 오답인데 길이만으로 필터링됐다는 점을 지적했다. 0.6B 학생 모델 학습 시 정답 트레이스만 남겼을 때 기존 33.6% 성능이 얼마나 달라지는지 검증해야 한다는 제안이다. https://x.com/yusufksadek/status/2111516335817756958 #deepseek #

    ainews@[email protected]♥ 0↻ 02026-10-18 08:51 UTCView post →

#trainingdata across platforms

every network with a public tag surface

Follow #trainingdata 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/trainingdata