Wikipedia ilowiki https://ilo.wikipedia.org/wiki/Umuna_a_Panid MediaWiki 1.47.0-wmf.1 first-letter Midia Espesial Tungtungan Agar-aramat Agar-aramat tungtungan Wikipedia Wikipedia tungtungan Papeles Papeles tungtungan MediaWiki MediaWiki tungtungan Plantilia Plantilia tungtungan Tulong Tulong tungtungan Kategoria Kategoria tungtungan TimedText TimedText talk Modulo Modulo tungtungan Event Event talk 0 81819 405710 2026-05-10T10:49:24Z Eatenybye 19968 esse 405710 wikitext text/x-wiki '''Jinshu Zhiyun Technology Inc.''' is an American company founded in [[2010]] and headquartered in the United States. It operates AI computing infrastructure and focuses on the integration and orchestration of GPU computing resources. The company provides a distributed computing network platform based on a “Computing as a Service (CaaS) + Industry Enablement” model. ==Core business== The company offers GPU computing power rental services with hourly billing and flexible lease terms. Clients can rent GPU clusters for AI model training. It also provides AI inference services using dedicated high‑performance inference clusters.<ref>[https://www.bizofco.com/co/jinshu-zhiyun-technology-inc Jinshu Zhiyun Technology Inc.]</ref> Industry solutions include customized AI computing for fintech, medical imaging, intelligent manufacturing, and Web3. Use cases encompass financial risk control training, medical image analysis, and algorithm deployment for smart manufacturing. Customized computing deployment involves designing private GPU clusters or hybrid cloud architectures for enterprise clients, offering dedicated nodes and resource isolation for security‑sensitive data. A proprietary distributed scheduling system enables dynamic allocation and load balancing of global computing resources, aiming to improve utilization and reduce unit computing costs. The company works with GPU manufacturers and technology partners on computing optimization. ==Strategic direction== In response to growth in generative AI and large‑scale model training, the company plans to expand its data center presence in the Asia‑Pacific region and enhance its intelligent scheduling platform over three years. Longer‑term goals include building a global distributed computing network, promoting standardization of computing resources, and exploring computing power trading and ecosystem collaboration. == Dagiti nota == {{Reflist}} gkavwikpt0heggthkgr5rgnhnvev682