#cudax

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

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Own #cudax

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$1,129.43/ year · 5-character #name
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0
Uses / 7 days
Mastodon
0
Accounts / 7 days
Mastodon
4
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 4
0
Avg reactions / post
Mastodon · last 4

Day-by-day usage

measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-27 11:38 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 11:38 UTC

No related tags with measured usage found for #cudax.

Live pulse

measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-27 11:38 UTC

Everything below is measured over the latest 4 public posts (spanning ~9580 hours).

Posting hours (UTC)

00:0012:0023:00

Languages: English (2)

Avg boosts / post: 0

Top of the latest posts

  • NVIDIA Europe (@NVIDIAEU) ISC26에서 CUDA-X 소프트웨어 cuPhoton, DAQIRI, ALCHEMI를 공개했다. 천문 데이터 분석을 최대 15,000배 가속하고, 물질 발견 등 과학 연구를 실시간 인사이트 수준으로 단축하는 것이 핵심이다. AI/ML 개발자 관점에선 GPU 기반 과학 컴퓨팅·데이터 처리 가속 인프라의 실전 활용 사례로 볼 수 있다. https://x.com/NVIDIAEU/stat

    ainews@[email protected]♥ 0↻ 02026-06-22 20:54 UTCView post →

  • NVIDIA (@nvidia) Jensen Huang이 CUDA-X 생태계가 현대 과학·공학의 돌파구를 뒷받침한다고 언급했다. cuOpt, Parabricks 등 1,000개가 넘는 CUDA-X 라이브러리가 다양한 분야의 개발자들이 혁신을 만들도록 돕는다는 메시지로, NVIDIA의 개발자용 AI/컴퓨팅 플랫폼의 중요성을 강조한다. https://x.com/nvidia/status/2048854700682825797 #nvidi

    ainews@[email protected]♥ 0↻ 02026-04-28 13:44 UTCView post →

  • NVIDIA DGX Spark and DGX Station Power the Latest Open-Source and Frontier Models From the Desktop Open-source AI is accelerating innovation across industries, and NVIDIA DGX Spark and DGX Station ... #Data #Center #Artificial #Intelligence

    deepseek@[email protected]♥ 0↻ 02026-01-05 22:49 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/cudax