[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"news-3de0fc02-b400-4c9a-a613-426b5004b27b":3},{"id":4,"title":5,"summary":6,"original_url":7,"source_id":8,"tags":9,"published_at":23,"created_at":24,"modified_at":25,"is_published":26,"publish_type":27,"image_url":13,"view_count":28},"3de0fc02-b400-4c9a-a613-426b5004b27b","NASA 和 IBM 的 Prithvi：首个在轨 AI 地理空间基础模型开启遥感新范式","2026年5月，阿德莱德大学与 SmartSat 合作研究中心的团队成功将 NASA 与 IBM 联合开发的开源地理空间基础模型 Prithvi 部署至两颗在轨平台——南澳政府的 Kanyini 卫星及国际空间站的 IMAGIN-e 载荷，成为首个在轨运行的地理空间 AI 基础模型。\n\nPrithvi 基于 Landsat 与 Sentinel-2 卫星 13 年遥感数据训练，具备跨任务泛化能力，可适配洪水监测、云层识别、作物估产等多种下游任务。核心突破在于：传统卫星受带宽限制，上传新模型几乎不可能，而 Prithvi 仅需补充一个小型解码器扩展包即可完成任务适配，大幅降低了在轨更新的门槛。\n\n开源策略同样关键。研究负责人 Dr. Andrew Du 直言：「若 Prithvi 不是开源的，我必须从零训练自己的基础模型。」NASA 与 IBM 的开放路线让全球研究者能快速复用与创新，验证了基础模型理念的价值。\n\nNASA 还计划发布行星科学、天体物理等更多领域的基础模型，继续拓展 AI for Science 的边界。","https:\u002F\u002Fscience.nasa.gov\u002Fscience-research\u002Fai-foundation-model-in-orbit\u002F","13624c51-a5f5-45bf-871b-b74b42216182",[10,14,17,20],{"id":11,"name":12,"slug":12,"description":13,"color":13},"e676a5cf-1f24-472f-a765-86fa21a1bc3c","ai-model",null,{"id":15,"name":16,"slug":16,"description":13,"color":13},"5e628969-6d2a-437f-998a-104e4b16cfb1","ai-progress",{"id":18,"name":19,"slug":19,"description":13,"color":13},"499f4b56-819d-49a3-9609-33e775143b86","multimodal",{"id":21,"name":22,"slug":22,"description":13,"color":13},"b9bd9039-fcdb-41a8-b85b-fc1587def2b9","open-source","2026-05-07T11:00:00Z","2026-05-07T19:05:24.336910Z","2026-05-07T19:05:24.336920Z",true,"agent",3]