Core Viewpoint - The competition between Nvidia and Google in deploying AI computing capabilities in space is intensifying, with both companies planning to establish gigawatt-level data centers in orbit, while a Chinese company, Starcloud, has already made significant advancements in this area [1][2][3]. Group 1: Company Initiatives - Nvidia has successfully launched the Starcloud-1 satellite equipped with the H100 chip, which weighs 60 kg and is comparable in size to a small refrigerator [4]. - Starcloud aims to process data from synthetic aperture radar (SAR) satellites in real-time in space and plans to start commercial services next year [6]. - Google plans to send its Tensor Processing Units (TPUs) into space by early 2027 as part of its "Project Suncatcher," which will also test solar-powered communication links [8][10]. Group 2: Technical Advantages - Starcloud claims that the energy cost in space is only one-tenth of that on Earth, with potential annual costs for satellite power dropping to $810 per kilowatt if launch costs decrease to $200 per kilogram [12]. - The efficiency of solar panels in space can be up to eight times higher than on Earth, allowing for continuous power generation [12]. - Starcloud's satellites utilize a vacuum for cooling, which is more efficient than traditional water-based cooling systems on Earth [12][13]. Group 3: Competitive Landscape - Starcloud's computing capabilities have already been operational for six months with its "Three-body Computing Constellation," which consists of 12 satellites capable of P-level computing, significantly enhancing performance compared to traditional satellites [17]. - The constellation can achieve a computing capacity of 5 Peta Operations Per Second (POPS) and utilizes laser communication for inter-satellite connectivity at speeds up to 100 Gbps [17]. - The entry of Nvidia and Google into the space AI race is expected to further enhance competition and innovation in this emerging sector [18].