#autoresearch

Live, measured metrics for the hashtag #autoresearch from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.

hashtag.org network · sponsored

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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.

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0
Uses / 7 days
Mastodon
0
Accounts / 7 days
Mastodon
24
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 24
0
Avg reactions / post
Mastodon · last 24

Day-by-day usage

measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-27 05:28 UTC
0
07-21
0
07-22
0
07-23
0
07-24
0
07-25
0
07-26
0
07-27

0 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 05:28 UTC
#autoresearch_at_home
0 uses · 0 accounts / 7d

Live pulse

measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-27 05:28 UTC

Everything below is measured over the latest 24 public posts (spanning ~2652 hours).

Posting hours (UTC) — busiest: 16:00

00:0012:0023:00

Languages: English (23) · Italian (1)

Avg boosts / post: 0

Top of the latest posts

  • Wes Roth (@WesRoth) Sakana AI Labs의 'Fugu'가 AutoResearch에서 좋은 성능을 보였고, GPT-5.5와 Opus 4.8보다 낫다고 주장합니다. 또한 Sam Altman이 OpenAI 모델 일부로 설계된 AI 추론 칩 'Jalapeno'를 공개했다는 언급이 포함되어 있어, 모델 성능과 AI 하드웨어/추론 인프라 측면에서 주목할 만합니다. https://x.com/WesRoth/status/

    ainews@[email protected]♥ 0↻ 02026-06-26 05:44 UTCView post →

  • Jim Fan (@DrJimFan) ENPIRE를 통해 물리 세계에서의 AutoResearch를 처음으로 활성화했다고 소개했습니다. 8개의 Codex 에이전트에 로봇 플릿, GPU 자원, 충분한 토큰 예산을 주고 빠르게 과제를 해결하도록 하는 설정으로, LLM 에이전트의 로보틱스·자율 실험 방향을 보여줍니다. https://x.com/DrJimFan/status/2066921736369766762 #codex #agents #

    ainews@[email protected]♥ 0↻ 02026-06-16 22:49 UTCView post →

  • Can LLMs Beat Classical Hyperparameter Optimization Algorithms? 본 논문은 LLM 기반 하이퍼파라미터 최적화(HPO) 방법과 전통적 알고리즘(CMA-ES, TPE)을 비교 분석했다. LLM은 코드 직접 편집을 통해 최적화를 시도하지만, 메모리 오류 회피가 중요한 상황에서 전통적 방법이 더 우수했다. 저자들은 LLM과 CMA-ES의 장점을 결합한 하이브리드 'Centaur'를 제

    ainews@[email protected]♥ 0↻ 02026-06-09 22:41 UTCView post →

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/autoresearch