#aiscaling

Live, measured metrics for the hashtag #aiscaling 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 #aiscaling

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.

$51.02/ year · 9-character #name
Claim #aiscaling — $51.02/yr→Buy on hashtag.space (web3)
card via hashtag.org · tokens via hashtag.space
0
Uses / 7 days
Mastodon
0
Accounts / 7 days
Mastodon
9
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 9
0
Avg reactions / post
Mastodon · last 9
—
Reddit posts / month
Reddit search
—
Open-web mentions
hashtag.org Firehose

Day-by-day usage

measured · mas.to (Mastodon public tags API) · fetched 2026-10-30 10:53 UTC
0
10-24
0
10-25
0
10-26
0
10-27
0
10-28
0
10-29
0
10-30

0 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 2026-10-30 10:53 UTC

Live pulse

measured · mas.to (Mastodon tag timeline) · fetched 2026-10-30 10:53 UTC

Everything below is measured over the latest 9 public posts (spanning ~13108 hours).

Top of the latest posts

  • https://www.europesays.com/people/231767/ You don’t need to write prompts for ChatGPT, Sam Altman reveals a secret #AIForStudents #AIScaling #AIUtility #AutomatedCoding #ChatGPT #GPT3 #OpenAI #SamAltman #YCombinator

    People@[email protected]♥ 0↻ 02026-09-17 15:28 UTCView post →
  • Rohan Paul (@rohanpaul_ai) Zhipu 창업자 Tang Jie의 글을 인용하며, AI 모델 스케일링이 단순 파라미터 수 증가를 넘어섰다고 지적합니다. 모델 역량은 파라미터뿐 아니라 학습 데이터와 추론 1회당 컴퓨트 등 여러 독립적인 축의 조합으로 평가해야 한다는 관점입니다. https://x.com/rohanpaul_ai/status/2090415822741426237 #aiscaling #llm #mode

    ainews@[email protected]♥ 0↻ 02026-08-20 12:54 UTCView post →
  • Condorcet의 배심원 정리에 따르면 각 전문가가 p>0.5일 때 다수결은 N 증가에 따라 정답 확률(j)을 급격히 높인다. 생성형 AI를 병렬로 여러 번 실행해 'AI 배심원'을 구성하면 p만 조금 넘겨도 높은 최종 정확도를 비용으로 확보할 수 있다. 코드 검사·문서·스타일 판정 같은 이진 판단에 유용하지만 응답의 독립성 가정은 약점이다. https://www.anthropic.com/news/fable-mythos-ac

    ainews@[email protected]♥ 0↻ 02026-06-13 03:38 UTCView post →

#aiscaling across platforms

every network with a public tag surface

Follow #aiscaling 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/aiscaling