{"@context":"https://schema.org","@type":"NewsArticle","generatedAt":"2026-07-28T05:20:57.982Z","headline":"NVIDIA 开源首个 GPU 加速医疗物理仿真框架","description":"NVIDIA 宣布开源 Medical Physics Simulation 框架，这是 Isaac for Healthcare 中首个 GPU 加速的医疗物理仿真能力。该框架可并行运行 8，192 个机器人训练环境，将训练时间从超过 5 小时缩短至不到 2 分钟。CMR Surgical、Johnson & Johnson MedTech 等机构已在使用该框架。","url":"https://www.aioga.com/news/cms3fbu4z00h6rond0qo6j75s/","mainEntityOfPage":"https://www.aioga.com/news/cms3fbu4z00h6rond0qo6j75s/","datePublished":"2026-07-22T13:00:11.000Z","dateModified":"2026-07-22T13:00:11.000Z","inLanguage":"zh-CN","publisher":{"@type":"NewsMediaOrganization","name":"Aioga","url":"https://www.aioga.com"},"citation":["https://blogs.nvidia.com/blog/medical-physics-simulation-open-source","https://aihot.virxact.com/items/cms3fbu4z00h6rond0qo6j75s"],"canonicalUrl":"https://www.aioga.com/news/cms3fbu4z00h6rond0qo6j75s/","directAnswer":{"@type":"Answer","text":"NVIDIA 宣布开源 Medical Physics Simulation，称其为 Isaac for Healthcare 中首个 GPU 加速医疗物理仿真能力。摘要显示，该框架可并行运行 8,192 个机器人训练环境，并将训练时间从超过5小时缩短至不到2分钟。","url":"https://www.aioga.com/news/cms3fbu4z00h6rond0qo6j75s/","dateCreated":"2026-07-22T13:00:11.000Z","author":{"@type":"Organization","@id":"https://www.aioga.com/authors/aioga-editorial/#editorial-team","name":"Aioga Editorial Team","url":"https://www.aioga.com/authors/aioga-editorial/"}},"evidence":[{"@type":"CreativeWork","name":"blogs.nvidia.com source article","url":"https://blogs.nvidia.com/blog/medical-physics-simulation-open-source","datePublished":"2026-07-22T13:00:11.000Z","provider":{"@type":"Organization","name":"blogs.nvidia.com","url":"https://blogs.nvidia.com/blog/medical-physics-simulation-open-source"}},{"@type":"CreativeWork","name":"AIHot archive record","url":"https://aihot.virxact.com/items/cms3fbu4z00h6rond0qo6j75s","datePublished":"2026-07-22T13:00:11.000Z","provider":{"@type":"Organization","name":"AIHot","url":"https://aihot.virxact.com/items/cms3fbu4z00h6rond0qo6j75s"}}],"aggregationSource":"NVIDIA Blog（RSS）","originalPublisher":{"name":"blogs.nvidia.com","url":"https://blogs.nvidia.com/blog/medical-physics-simulation-open-source"},"article":{"id":"cms3fbu4z00h6rond0qo6j75s","slug":"cms3fbu4z00h6rond0qo6j75s","url":"https://www.aioga.com/news/cms3fbu4z00h6rond0qo6j75s/","title":"NVIDIA 开源首个 GPU 加速医疗物理仿真框架","title_en":"NVIDIA Open Sources First GPU-Accelerated Medical Physics Simulation Framework","summary":"NVIDIA 宣布开源 Medical Physics Simulation 框架，这是 Isaac for Healthcare 中首个 GPU 加速的医疗物理仿真能力。该框架可并行运行 8，192 个机器人训练环境，将训练时间从超过 5 小时缩短至不到 2 分钟。CMR Surgical、Johnson & Johnson MedTech 等机构已在使用该框架。","source":"NVIDIA Blog（RSS）","sourceUrl":"https://blogs.nvidia.com/blog/medical-physics-simulation-open-source","aiHotUrl":"https://aihot.virxact.com/items/cms3fbu4z00h6rond0qo6j75s","publishedAt":"2026-07-22T13:00:11.000Z","category":"产品更新","score":60,"selected":true,"articleBody":["Before a healthcare robot can be useful in the real world, it has to learn how the physical world pushes back. Anatomy varies. Instruments bend, press, slip and interact with tissue. Imaging can be noisy or incomplete. And the rare, edge scenarios developers most need to understand don’t appear on schedule.","That creates one of the biggest bottlenecks in healthcare robotics: obtaining the enormous amount of varied data developers need to train, test and improve robot behavior.","NVIDIA Medical Physics Simulation framework — a new open source, GPU-accelerated capability within NVIDIA Isaac for Healthcare — announced today, helps medical robotics developers model anatomy-device interaction, generate hard-to-capture scenarios, test in silico, and train or evaluate robot policies before hardware-heavy testing.","The framework brings together anatomy and medical device behavior with sensor simulation and robot learning so teams can create reusable simulation environments instead of rebuilding custom scenes for every workflow, saving developers time and bringing innovations to market faster.","Because Medical Physics Simulation is open source, healthcare robotics developers can inspect the framework, adapt it to their own devices and workflows, and build on a GPU-accelerated foundation that works seamlessly with the broader NVIDIA stack.","Open source is especially important in healthcare because teams need transparency into the data, models and weights that shape system behavior. Access to open models and model weights can help developers reproduce results, evaluate performance across different anatomies and scenarios, identify limitations and build evidence for regulatory review.","For physical AI ：https://www.nvidia.com/en-us/glossary/generative-physical-ai/ , experience is data in motion. Developers need to train robots to operate properly even when anatomy changes, devices behave differently, conditions shift or a policy fails unexpectedly.","Medical Physics Simulation helps developers simulate anatomy, device contact, friction and sensor inputs, then test in interactions and environments to evaluate how robots perform across those changes. Powered by NVIDIA CUDA and part of Isaac for Healthcare — built on the NVIDIA Warp, Newton and Cosmos simulation and generative AI technologies — the framework can run hundreds of parallel simulation environments, helping teams explore more scenarios and identify failure modes earlier in development.","For robot builders, this turns simulation from a bespoke engineering project into reusable infrastructure. The difference now is scale: benchmarks ：https://arxiv.org/abs/2503.18616 show 8,192 robot-training environments running in parallel with GPU-native simulation cut training from over five hours to under two minutes.","With this framework, developers can connect vascular anatomy, flexible instruments such as catheters and guidewires, simulated X-ray imaging and reinforcement learning. The framework is designed to extend beyond that example to additional devices, anatomies, sensors and healthcare robotics domains.","Medical Physics Simulation brings together classical physics simulation and generative AI physics simulation. Classical simulation helps model known physical rules, such as device contact, friction and motion. NVIDIA Cosmos-H Dreams：https://github.com/isaac-for-healthcare/Cosmos-H-Dreams, the real-time generative AI physics simulation capability within Medical Physics Simulation, helps model visual scene dynamics learned from procedural data.","Together, these approaches give developers a richer way to build and test healthcare robotics systems in virtual environments before moving to physical prototypes and lab testing.","Medical robotics leaders are already applying simulation-driven development to solve specific surgical challenges .","CMR Surgical and Cambridge Consultants, part of Capgemini, are using Cosmos-H-Dreams to implicitly learn interaction physics for soft-tissue surgical procedures and generate patient-specific simulations. CMR contributed nearly 500 hours of anonymized clinical data from its Versius Surgical Robotic System to the Open-H Embodiment open dataset, benefiting procedures including cholecystectomy, prostatectomy, hernia repair and hysterectomy.","“Open source models allow us to build on shared knowledge, accelerating responsible innovation and, ultimately, gives us the potential to deliver more consistent care and better outcomes for patients worldwide,” said Chris Fryer, chief technology officer at CMR Surgical.","Johnson & Johnson MedTech i s using Isaac for Healthcare’s Medical Physics Simulation and a Cosmos-based foundation model to build digital twins of its endoluminal MONARCH platform for urology, modeling complex anatomy and kidney-stone scenarios. XCath is using the Medical Physics Simulation for endovascular autonomy policy training. Inner Logic i s accelerating the evolution of medical technology with synthetic data, validating device mechanics and producing in silico evidence to support regulatory pathways with NVIDIA Medical Physical Simulation.","Medtronic Structural Heart is exploring applying Medical Physics Simulation with simulated X-ray sensing to generate data for catheter navigation research.","As a modular capability within NVIDIA Isaac for Healthcare, Medical Physics Simulation can be used on its own or alongside digital twin pipelines, medical sensor simulation, the NVIDIA Isaac Lab open robot-learning framework and NVIDIA open models and policies.","Developers can explore the open source Medical Physics Simulation framework ：https://isaac-for-healthcare.github.io/medical-physics-simulation/ , review available reference workflows and start building simulation environments for their own devices, anatomies and healthcare robotics applications."],"articleImages":[{"sourceUrl":"https://blogs.nvidia.com/wp-content/uploads/2026/06/gtc26-berlin-open-reg-mktg-kit-corp-blog-1920x1080-1-1-960x540.jpg","alt":"NVIDIA GTC Berlin Registration Is Now Open","afterParagraph":18,"url":"/media/articles/cms3fbu4z00h6rond0qo6j75s/fbad671ccf7f14b3.jpg"},{"sourceUrl":"https://blogs.nvidia.com/wp-content/uploads/2026/07/blog-1920x1080-no-copy.jpg","alt":"Sharpen the Sword, Skip the Downloads — ‘Onimusha: Way of the Sword’ Is Coming to GeForce NOW","afterParagraph":18,"url":"/media/articles/cms3fbu4z00h6rond0qo6j75s/da6b6adfc53b2a50.jpg"},{"sourceUrl":"https://blogs.nvidia.com/wp-content/uploads/2026/07/gfn-thursday-7-9-blog-1920x1080-no-copy.jpg","alt":"GeForce NOW Turns Up the Heat With New GeForce RTX 5080-Powered Toronto Server","afterParagraph":18,"url":"/media/articles/cms3fbu4z00h6rond0qo6j75s/e50b209dbb03a249.jpg"},{"sourceUrl":"https://blogs.nvidia.com/wp-content/uploads/2026/06/gfn-thursday-6-25-no-copy-kv-1536x920-1-400x225.jpg","alt":"The Ultimate Summer Sale Pairing: Steam Sale Meets GeForce NOW Discounts","afterParagraph":18,"url":"/media/articles/cms3fbu4z00h6rond0qo6j75s/8389199368e4dd4c.jpg"}],"mediaStatus":"ok","articleBodyZh":["在医疗机器人能够在现实世界中发挥作用之前，它必须学习物理世界的反作用。解剖结构存在差异。器械会弯曲、按压、滑动并与组织互动。成像可能存在噪声或不完整。而开发者最需要理解的罕见极端场景不会按计划出现。","这就造成了医疗机器人领域最大的瓶颈之一：获取开发者训练、测试和改进机器人行为所需的巨大而多样化的数据。","NVIDIA 医学物理仿真框架——NVIDIA Isaac for Healthcare 中的一个新的开源 GPU 加速能力——今日宣布，帮助医疗机器人开发者建模解剖与器械的交互，生成难以捕捉的场景，进行虚拟测试，并在硬件密集型测试前训练或评估机器人策略。","该框架将解剖学与医疗器械行为与传感器仿真及机器人学习结合在一起，使团队能够创建可重复使用的仿真环境，而无需为每个工作流程重建自定义场景，从而节省开发者时间并更快将创新推向市场。","由于医学物理仿真是开源的，医疗机器人开发者可以检查框架，适配到自己的设备和工作流程，并在 GPU 加速的基础上构建，与更广泛的 NVIDIA 技术栈无缝协作。","开源在医疗领域尤为重要，因为团队需要透明地了解塑造系统行为的数据、模型和权重。访问开放模型和模型权重可以帮助开发者复现结果，在不同解剖结构和场景下评估性能，识别局限性，并为监管审查建立证据。","对于物理 AI：https://www.nvidia.com/en-us/glossary/generative-physical-ai/，经验就是动态数据。开发者需要训练机器人在解剖变化、器械行为不同、条件变化或策略意外失效时也能正常操作。","医学物理仿真帮助开发者模拟解剖结构、设备接触、摩擦和传感器输入，然后在交互和环境中进行测试，以评估机器人在这些变化下的表现。该框架由 NVIDIA CUDA 提供支持，并且是 Isaac for Healthcare 的一部分——构建于 NVIDIA Warp、Newton 和 Cosmos 仿真及生成式人工智能技术之上——可以运行数百个并行仿真环境，帮助团队探索更多场景并在开发早期识别失败模式。","对于机器人开发者来说，这将仿真从定制工程项目转变为可重复使用的基础设施。现在的区别在于规模：基准测试（https://arxiv.org/abs/2503.18616）显示，8,192 个机器人训练环境并行运行，使用 GPU 原生仿真将训练时间从五个多小时缩短至不到两分钟。","利用该框架，开发者可以连接血管解剖结构、柔性器械（如导管和导丝）、模拟 X 光成像和强化学习。该框架被设计为不仅限于这些示例，还可扩展到其他设备、解剖结构、传感器和医疗机器人领域。","医学物理仿真将经典物理仿真与生成式 AI 物理仿真结合在一起。经典仿真有助于建模已知的物理规则，例如设备接触、摩擦和运动。NVIDIA Cosmos-H Dreams（https://github.com/isaac-for-healthcare/Cosmos-H-Dreams），这是医学物理仿真中的实时生成式 AI 物理仿真能力，帮助从程序化数据中学习并建模视觉场景动态。","这些方法结合在一起，为开发者在转向物理原型和实验室测试之前，在虚拟环境中构建和测试医疗机器人系统提供了更丰富的方法。","医疗机器人领域的领导者已经在利用仿真驱动开发来解决具体的手术挑战。","CMR Surgical 和 Capgemini 旗下的 Cambridge Consultants 正在使用 Cosmos-H-Dreams 来隐式学习软组织外科手术的交互物理，并生成患者特定的模拟。CMR 向 Open-H Embodiment 开放数据集贡献了其 Versius 外科机器人系统的近 500 小时匿名临床数据，惠及包括胆囊切除术、前列腺切除术、疝修补术和子宫切除术在内的手术操作。","CMR Surgical 首席技术官 Chris Fryer 表示：“开源模型使我们能够建立在共享知识的基础上，加速负责任的创新，并最终有可能为全球患者提供更一致的护理和更好的结果。”","强生医疗技术正在利用 Isaac for Healthcare 的医学物理模拟和基于 Cosmos 的基础模型来构建其泌尿外科 ENDOLUMINAL MONARCH 平台的数字孪生，模拟复杂的解剖结构和肾结石场景。XCath 正在使用医学物理模拟进行血管内自主策略训练。Inner Logic 通过合成数据加速医疗技术的发展，验证设备力学并生成体外证据以支持监管路径，利用 NVIDIA 医学物理模拟。","美敦力结构心脏部门正在探索将医学物理模拟与模拟 X 光感应技术结合应用，以生成导管导航研究的数据。","作为 NVIDIA Isaac for Healthcare 的模块化功能，医学物理模拟既可以单独使用，也可以与数字孪生管道、医疗传感器模拟、NVIDIA Isaac Lab 开放机器人学习框架以及 NVIDIA 开放模型和策略一起使用。","开发者可以浏览开源医学物理模拟框架：https://isaac-for-healthcare.github.io/medical-physics-simulation/，查看可用的参考工作流程，并开始为自己的设备、解剖结构和医疗机器人应用构建模拟环境。"],"translationStatus":"translated","bodyOrigin":"source-page","editorial":{"summary":"NVIDIA 宣布开源 Medical Physics Simulation，称其为 Isaac for Healthcare 中首个 GPU 加速医疗物理仿真能力。摘要显示，该框架可并行运行 8,192 个机器人训练环境，并将训练时间从超过5小时缩短至不到2分钟。","background":"医疗机器人开发需要处理解剖差异、器械与组织接触、传感器噪声及罕见场景，但相关训练和测试数据难以大量获取。该框架用于模拟解剖结构、设备接触、摩擦和传感器输入，并支持在硬件密集型测试前训练或评估机器人策略。","viewpoint":"Aioga 判断，开源与 GPU 并行仿真的组合，可能降低医疗机器人团队重复搭建定制场景的成本，并扩大早期测试覆盖面。但材料中的性能数字来自 NVIDIA 摘要，尚不足以推定其适用于所有设备、工作流或临床环境。","implications":"开发者可检查并调整框架，使其适配自身设备和工作流，也可能更早识别策略失效情形。材料还称，开放模型和权重有助于复现结果、评估不同解剖场景、识别局限，并为监管审查积累证据。","nextStep":"值得关注后续是否公开基准测试条件、硬件配置、场景复杂度及复现方法，并观察 CMR Surgical、Johnson & Johnson MedTech 等使用机构是否披露具体应用结果、局限和验证证据。","evidenceRefs":["title","summary","articleBody","source"],"status":"published","aiGenerated":true,"autoApproved":true,"generatedBy":"aioga-editorial:gpt-5.6-sol","reviewedBy":"aioga-editorial-review:gpt-5.6-sol","generatedAt":"2026-07-27T17:52:26.312Z","sourceHash":"0c1ba115c4f43c65","review":{"approved":true,"groundedness":96,"clarity":93,"duplicationRisk":18,"blockingIssues":[],"notes":["候选内容对 8,192 个并行训练环境及训练时间缩短的数字明确归因于 NVIDIA 摘要，并对其适用范围作出保留，处理恰当。","“降低……重复搭建定制场景的成本”属于已明确标注的分析判断；若需更贴近原文，可改为“减少重复搭建定制场景所需的时间和开发投入”，但不构成阻断问题。","nextStep 中对使用机构披露具体结果的期待属于后续观察建议，未冒充既成事实。"]},"validation":{"passed":true,"mode":"ai-auto","revisions":0,"checks":["schema","length","source-attribution","low-source-overlap","no-html","independent-ai-review"]}},"tags":["产品更新","NVIDIA Blog（RSS）"],"translations":{"zh-CN":{"title":"NVIDIA 开源首个 GPU 加速医疗物理仿真框架","summary":"NVIDIA 宣布开源 Medical Physics Simulation 框架，这是 Isaac for Healthcare 中首个 GPU 加速的医疗物理仿真能力。该框架可并行运行 8，192 个机器人训练环境，将训练时间从超过 5 小时缩短至不到 2 分钟。CMR Surgical、Johnson & Johnson MedTech 等机构已在使用该框架。","category":"产品更新","source":"blogs.nvidia.com","aggregationSource":"NVIDIA Blog（RSS）","pageTitle":"NVIDIA 开源首个 GPU 加速医疗物理仿真框架 - Aioga AI资讯","description":"NVIDIA 宣布开源 Medical Physics Simulation 框架，这是 Isaac for Healthcare 中首个 GPU 加速的医疗物理仿真能力。该框架可并行运行 8，192 个机器人训练环境，将训练时间从超过 5 小时缩短至不到 2 分钟。CMR Surgical、Johnson & Johnson MedTech 等机构已在使用...","url":"https://www.aioga.com/news/cms3fbu4z00h6rond0qo6j75s/"},"en":{"title":"NVIDIA Open-Sources Its First GPU-Accelerated Medical Physics Simulation Framework","summary":"NVIDIA announced the open-sourcing of the Medical Physics Simulation framework, which is the first GPU-accelerated medical physics simulation capability in Isaac for Healthcare. This framework can run 8,192 robot training environments in parallel, reducing training time from over 5 hours to less than 2 minutes. Institutions such as CMR Surgical and Johnson & Johnson MedTech are already using this framework.","category":"Products","source":"NVIDIA Blog（RSS）","aggregationSource":"NVIDIA Blog（RSS）","pageTitle":"NVIDIA Open-Sources Its First GPU-Accelerated Medical Physics Simulation Framework - Aioga AI News","description":"NVIDIA announced the open-sourcing of the Medical Physics Simulation framework, which is the first GPU-accelerated medical physics simulation capability in Isaac for Healthcare. Th...","url":"https://www.aioga.com/en/news/cms3fbu4z00h6rond0qo6j75s/","contentTranslated":true,"sourceHash":"15c4701651f53a9e","translatedAt":"2026-07-27T17:44:37.583Z"},"ja":{"title":"NVIDIA、初のGPU加速医療物理シミュレーションフレームワークをオープンソース化","summary":"NVIDIAはMedical Physics Simulationフレームワークのオープンソース化を発表しました。これはIsaac for Healthcareで初めてのGPU加速医療物理シミュレーション機能です。このフレームワークは8,192のロボット訓練環境を並列に実行でき、訓練時間を5時間以上から2分未満に短縮します。CMR Surgical、Johnson & Johnson MedTechなどの機関ですでに使用されています。","category":"製品更新","source":"NVIDIA Blog（RSS）","aggregationSource":"NVIDIA Blog（RSS）","pageTitle":"NVIDIA、初のGPU加速医療物理シミュレーションフレームワークをオープンソース化 - Aioga AIニュース","description":"NVIDIAはMedical Physics Simulationフレームワークのオープンソース化を発表しました。これはIsaac for Healthcareで初めてのGPU加速医療物理シミュレーション機能です。このフレームワークは8,192のロボット訓練環境を並列に実行でき、訓練時間を5時間以上から2分未満に短縮します。CMR Surgical、John...","url":"https://www.aioga.com/ja/news/cms3fbu4z00h6rond0qo6j75s/","contentTranslated":true,"sourceHash":"15c4701651f53a9e","translatedAt":"2026-07-27T17:44:45.615Z"},"ko":{"title":"NVIDIA가 최초의 GPU 가속 의료 물리 시뮬레이션 프레임워크를 오픈소스로 공개","summary":"NVIDIA는 오픈소스 Medical Physics Simulation 프레임워크를 발표했으며, 이는 Isaac for Healthcare에서 처음으로 GPU 가속 의료 물리 시뮬레이션 기능입니다. 이 프레임워크는 8,192개의 로봇 훈련 환경을 병렬로 실행할 수 있으며, 훈련 시간을 5시간 이상에서 2분 미만으로 단축합니다. CMR Surgical, Johnson & Johnson MedTech 등 기관이 이미 이 프레임워크를 사용하고 있습니다.","category":"제품 업데이트","source":"NVIDIA Blog（RSS）","aggregationSource":"NVIDIA Blog（RSS）","pageTitle":"NVIDIA가 최초의 GPU 가속 의료 물리 시뮬레이션 프레임워크를 오픈소스로 공개 - Aioga AI 뉴스","description":"NVIDIA는 오픈소스 Medical Physics Simulation 프레임워크를 발표했으며, 이는 Isaac for Healthcare에서 처음으로 GPU 가속 의료 물리 시뮬레이션 기능입니다. 이 프레임워크는 8,192개의 로봇 훈련 환경을 병렬로 실행할 수 있으며, 훈련 시간을 5시간 이상에서 2분 미만으로 단축합...","url":"https://www.aioga.com/ko/news/cms3fbu4z00h6rond0qo6j75s/","contentTranslated":true,"sourceHash":"15c4701651f53a9e","translatedAt":"2026-07-27T17:45:33.937Z"},"es":{"title":"NVIDIA lanza el primer marco de simulación de física médica acelerado por GPU de código abierto","summary":"NVIDIA ha anunciado la apertura del código del marco de simulación de física médica, que es la primera capacidad de simulación de física médica acelerada por GPU en Isaac para Healthcare. Este marco puede ejecutar en paralelo 8,192 entornos de entrenamiento de robots, reduciendo el tiempo de entrenamiento de más de 5 horas a menos de 2 minutos. Instituciones como CMR Surgical y Johnson & Johnson MedTech ya están utilizando este marco.","category":"Productos","source":"NVIDIA Blog（RSS）","aggregationSource":"NVIDIA Blog（RSS）","pageTitle":"NVIDIA lanza el primer marco de simulación de física médica acelerado por GPU de código abierto - Aioga Noticias de IA","description":"NVIDIA ha anunciado la apertura del código del marco de simulación de física médica, que es la primera capacidad de simulación de física médica acelerada por GPU en Isaac para Heal...","url":"https://www.aioga.com/es/news/cms3fbu4z00h6rond0qo6j75s/","contentTranslated":true,"sourceHash":"15c4701651f53a9e","translatedAt":"2026-07-27T17:45:31.995Z"},"fr":{"title":"NVIDIA ouvre en source le premier cadre de simulation de physique médicale accéléré par GPU","summary":"NVIDIA a annoncé l'ouverture de son cadre de simulation de physique médicale, il s'agit de la première capacité de simulation de physique médicale accélérée par GPU dans Isaac for Healthcare. Ce cadre peut faire fonctionner en parallèle 8 192 environnements d'entraînement pour robots, réduisant le temps d'entraînement de plus de 5 heures à moins de 2 minutes. Des institutions telles que CMR Surgical et Johnson & Johnson MedTech utilisent déjà ce cadre.","category":"Produits","source":"NVIDIA Blog（RSS）","aggregationSource":"NVIDIA Blog（RSS）","pageTitle":"NVIDIA ouvre en source le premier cadre de simulation de physique médicale accéléré par GPU - Aioga Actualités IA","description":"NVIDIA a annoncé l'ouverture de son cadre de simulation de physique médicale, il s'agit de la première capacité de simulation de physique médicale accélérée par GPU dans Isaac for...","url":"https://www.aioga.com/fr/news/cms3fbu4z00h6rond0qo6j75s/","contentTranslated":true,"sourceHash":"15c4701651f53a9e","translatedAt":"2026-07-27T17:46:14.847Z"},"de":{"title":"NVIDIA veröffentlicht das erste GPU-beschleunigte Simulations-Framework für medizinische Physik als Open Source","summary":"NVIDIA hat die Open-Source-Simulationsplattform für medizinische Physik angekündigt. Dies ist die erste GPU-beschleunigte medizinische Physiksimulationsfunktion in Isaac for Healthcare. Die Plattform kann 8.192 Roboter-Trainingsumgebungen parallel ausführen und die Trainingszeit von über 5 Stunden auf weniger als 2 Minuten verkürzen. Institutionen wie CMR Surgical und Johnson & Johnson MedTech nutzen die Plattform bereits.","category":"产品更新","source":"NVIDIA Blog（RSS）","aggregationSource":"NVIDIA Blog（RSS）","pageTitle":"NVIDIA veröffentlicht das erste GPU-beschleunigte Simulations-Framework für medizinische Physik als Open Source - Aioga KI-News","description":"NVIDIA hat die Open-Source-Simulationsplattform für medizinische Physik angekündigt. Dies ist die erste GPU-beschleunigte medizinische Physiksimulationsfunktion in Isaac for Health...","url":"https://www.aioga.com/de/news/cms3fbu4z00h6rond0qo6j75s/","contentTranslated":true,"sourceHash":"15c4701651f53a9e","translatedAt":"2026-07-27T17:46:13.536Z"},"pt-BR":{"title":"NVIDIA abre o código do primeiro framework de simulação de física médica acelerado por GPU","summary":"A NVIDIA anunciou a abertura do código do framework de Simulação de Física Médica, que é a primeira capacidade de simulação de física médica acelerada por GPU no Isaac for Healthcare. Esse framework pode executar paralelamente 8.192 ambientes de treinamento de robôs, reduzindo o tempo de treinamento de mais de 5 horas para menos de 2 minutos. Instituições como CMR Surgical e Johnson & Johnson MedTech já estão usando esse framework.","category":"产品更新","source":"NVIDIA Blog（RSS）","aggregationSource":"NVIDIA Blog（RSS）","pageTitle":"NVIDIA abre o código do primeiro framework de simulação de física médica acelerado por GPU - Aioga Notícias de IA","description":"A NVIDIA anunciou a abertura do código do framework de Simulação de Física Médica, que é a primeira capacidade de simulação de física médica acelerada por GPU no Isaac for Healthca...","url":"https://www.aioga.com/pt-BR/news/cms3fbu4z00h6rond0qo6j75s/","contentTranslated":true,"sourceHash":"15c4701651f53a9e","translatedAt":"2026-07-27T17:46:54.733Z"},"ru":{"title":"NVIDIA открывает первый фреймворк для медицинской физики с ускорением на GPU с открытым исходным кодом","summary":"NVIDIA объявила об открытии исходного кода фреймворка для медицинской физики Simulation, это первая возможность медицинской физики с ускорением на GPU в Isaac for Healthcare. Этот фреймворк может параллельно запускать 8 192 тренировочных среды для роботов, сокращая время обучения с более чем 5 часов до менее чем 2 минут. Такие организации, как CMR Surgical и Johnson & Johnson MedTech, уже используют этот фреймворк.","category":"产品更新","source":"NVIDIA Blog（RSS）","aggregationSource":"NVIDIA Blog（RSS）","pageTitle":"NVIDIA открывает первый фреймворк для медицинской физики с ускорением на GPU с открытым исходным кодом - Aioga Новости ИИ","description":"NVIDIA объявила об открытии исходного кода фреймворка для медицинской физики Simulation, это первая возможность медицинской физики с ускорением на GPU в Isaac for Healthcare. Этот...","url":"https://www.aioga.com/ru/news/cms3fbu4z00h6rond0qo6j75s/","contentTranslated":true,"sourceHash":"15c4701651f53a9e","translatedAt":"2026-07-27T17:47:01.349Z"},"ar":{"title":"NVIDIA تفتح المصدر لأول إطار محاكاة فيزيائية طبية معزز بوحدة معالجة الرسوميات","summary":"أعلنت NVIDIA عن إطلاق إطار عمل مفتوح المصدر لمحاكاة الفيزياء الطبية، وهو أول قدرة لمحاكاة الفيزياء الطبية مع تسريع GPU ضمن Isaac للرعاية الصحية. يمكن لهذا الإطار تشغيل 8,192 بيئة تدريب روبوتية بالتوازي، مما يقلل وقت التدريب من أكثر من 5 ساعات إلى أقل من دقيقتين. تستخدم مؤسسات مثل CMR Surgical و Johnson & Johnson MedTech هذا الإطار بالفعل.","category":"产品更新","source":"NVIDIA Blog（RSS）","aggregationSource":"NVIDIA Blog（RSS）","pageTitle":"NVIDIA تفتح المصدر لأول إطار محاكاة فيزيائية طبية معزز بوحدة معالجة الرسوميات - Aioga أخبار الذكاء الاصطناعي","description":"أعلنت NVIDIA عن إطلاق إطار عمل مفتوح المصدر لمحاكاة الفيزياء الطبية، وهو أول قدرة لمحاكاة الفيزياء الطبية مع تسريع GPU ضمن Isaac للرعاية الصحية. يمكن لهذا الإطار تشغيل 8,192 بيئة ت...","url":"https://www.aioga.com/ar/news/cms3fbu4z00h6rond0qo6j75s/","contentTranslated":true,"sourceHash":"15c4701651f53a9e","translatedAt":"2026-07-27T17:47:49.148Z"},"hi":{"title":"NVIDIA ने पहला GPU-संवर्धित चिकित्सा भौतिकी सिमुलेशन फ्रेमवर्क ओपन सोर्स किया","summary":"NVIDIA ने मेडिकल फिजिक्स सिमुलेशन फ्रेमवर्क को ओपन-सोर्स करने की घोषणा की, जो Isaac for Healthcare में पहला GPU-त्वरित मेडिकल फिजिक्स सिमुलेशन क्षमता है। यह फ्रेमवर्क 8,192 रोबोट प्रशिक्षण वातावरण को समांतर चलाने में सक्षम है, जिससे प्रशिक्षण समय 5 घंटे से अधिक से घटाकर 2 मिनट से कम कर दिया गया है। CMR Surgical, Johnson & Johnson MedTech जैसी संस्थाएं पहले से ही इस फ्रेमवर्क का उपयोग कर रही हैं।","category":"产品更新","source":"NVIDIA Blog（RSS）","aggregationSource":"NVIDIA Blog（RSS）","pageTitle":"NVIDIA ने पहला GPU-संवर्धित चिकित्सा भौतिकी सिमुलेशन फ्रेमवर्क ओपन सोर्स किया - Aioga AI समाचार","description":"NVIDIA ने मेडिकल फिजिक्स सिमुलेशन फ्रेमवर्क को ओपन-सोर्स करने की घोषणा की, जो Isaac for Healthcare में पहला GPU-त्वरित मेडिकल फिजिक्स सिमुलेशन क्षमता है। यह फ्रेमवर्क 8,192 रोबोट प...","url":"https://www.aioga.com/hi/news/cms3fbu4z00h6rond0qo6j75s/","contentTranslated":true,"sourceHash":"15c4701651f53a9e","translatedAt":"2026-07-27T17:47:44.708Z"},"it":{"title":"NVIDIA apre il primo framework di simulazione fisica medica accelerato dalla GPU","summary":"NVIDIA ha annunciato l'open source del framework di simulazione di fisica medica, che rappresenta la prima capacità di simulazione di fisica medica accelerata dalla GPU in Isaac for Healthcare. Questo framework può eseguire in parallelo 8.192 ambienti di addestramento robotico, riducendo il tempo di addestramento da oltre 5 ore a meno di 2 minuti. Organizzazioni come CMR Surgical e Johnson & Johnson MedTech stanno già utilizzando questo framework.","category":"产品更新","source":"NVIDIA Blog（RSS）","aggregationSource":"NVIDIA Blog（RSS）","pageTitle":"NVIDIA apre il primo framework di simulazione fisica medica accelerato dalla GPU - Aioga Notizie IA","description":"NVIDIA ha annunciato l'open source del framework di simulazione di fisica medica, che rappresenta la prima capacità di simulazione di fisica medica accelerata dalla GPU in Isaac fo...","url":"https://www.aioga.com/it/news/cms3fbu4z00h6rond0qo6j75s/","contentTranslated":true,"sourceHash":"15c4701651f53a9e","translatedAt":"2026-07-27T17:48:33.829Z"},"nl":{"title":"NVIDIA lanceert het eerste open-source GPU-versnelde simulatiekader voor medische fysica","summary":"NVIDIA heeft het open source Medical Physics Simulation-framework aangekondigd, dit is de eerste GPU-versnelde medische fysicasimulatiecapaciteit binnen Isaac for Healthcare. Het framework kan 8.192 robottrainingsomgevingen parallel uitvoeren en verkort de trainingstijd van meer dan 5 uur tot minder dan 2 minuten. Instanties zoals CMR Surgical en Johnson & Johnson MedTech gebruiken dit framework al.","category":"产品更新","source":"NVIDIA Blog（RSS）","aggregationSource":"NVIDIA Blog（RSS）","pageTitle":"NVIDIA lanceert het eerste open-source GPU-versnelde simulatiekader voor medische fysica - Aioga AI-nieuws","description":"NVIDIA heeft het open source Medical Physics Simulation-framework aangekondigd, dit is de eerste GPU-versnelde medische fysicasimulatiecapaciteit binnen Isaac for Healthcare. Het f...","url":"https://www.aioga.com/nl/news/cms3fbu4z00h6rond0qo6j75s/","contentTranslated":true,"sourceHash":"15c4701651f53a9e","translatedAt":"2026-07-27T17:48:34.026Z"},"tr":{"title":"NVIDIA, ilk GPU hızlandırmalı tıbbi fizik simülasyon çerçevesini açık kaynak yaptı","summary":"NVIDIA, Medical Physics Simulation çerçevesini açık kaynak olarak duyurdu. Bu, Isaac for Healthcare içindeki ilk GPU hızlandırmalı tıp fiziği simülasyon yeteneğidir. Bu çerçeve, 8.192 robot eğitim ortamını paralel olarak çalıştırabilir ve eğitim süresini 5 saatin üzerindense 2 dakikanın altına indirir. CMR Surgical, Johnson & Johnson MedTech gibi kurumlar bu çerçeveyi kullanmaktadır.","category":"产品更新","source":"NVIDIA Blog（RSS）","aggregationSource":"NVIDIA Blog（RSS）","pageTitle":"NVIDIA, ilk GPU hızlandırmalı tıbbi fizik simülasyon çerçevesini açık kaynak yaptı - Aioga AI Haberleri","description":"NVIDIA, Medical Physics Simulation çerçevesini açık kaynak olarak duyurdu. Bu, Isaac for Healthcare içindeki ilk GPU hızlandırmalı tıp fiziği simülasyon yeteneğidir. Bu çerçeve, 8....","url":"https://www.aioga.com/tr/news/cms3fbu4z00h6rond0qo6j75s/","contentTranslated":true,"sourceHash":"15c4701651f53a9e","translatedAt":"2026-07-27T17:49:20.694Z"},"vi":{"title":"NVIDIA mở mã nguồn khung mô phỏng vật lý y tế tăng tốc GPU đầu tiên","summary":"NVIDIA công bố nguồn mở khung mô phỏng Vật lý Y học, đây là khả năng mô phỏng vật lý y tế tăng tốc GPU đầu tiên trong Isaac for Healthcare. Khung này có thể chạy song song 8.192 môi trường đào tạo robot, rút ngắn thời gian đào tạo từ hơn 5 giờ xuống dưới 2 phút. Các tổ chức như CMR Surgical, Johnson & Johnson MedTech đã sử dụng khung này.","category":"产品更新","source":"NVIDIA Blog（RSS）","aggregationSource":"NVIDIA Blog（RSS）","pageTitle":"NVIDIA mở mã nguồn khung mô phỏng vật lý y tế tăng tốc GPU đầu tiên - Tin tức AI Aioga","description":"NVIDIA công bố nguồn mở khung mô phỏng Vật lý Y học, đây là khả năng mô phỏng vật lý y tế tăng tốc GPU đầu tiên trong Isaac for Healthcare. Khung này có thể chạy song song 8.192 mô...","url":"https://www.aioga.com/vi/news/cms3fbu4z00h6rond0qo6j75s/","contentTranslated":true,"sourceHash":"15c4701651f53a9e","translatedAt":"2026-07-27T17:49:22.658Z"},"id":{"title":"NVIDIA merilis kerangka simulasi fisika medis pertama yang dipercepat GPU secara open source","summary":"NVIDIA mengumumkan membuka kode sumber kerangka Simulasi Fisika Medis, ini adalah kemampuan simulasi fisika medis yang dipercepat GPU pertama dalam Isaac for Healthcare. Kerangka ini dapat menjalankan 8.192 lingkungan pelatihan robot secara paralel, mengurangi waktu pelatihan dari lebih dari 5 jam menjadi kurang dari 2 menit. Lembaga seperti CMR Surgical dan Johnson & Johnson MedTech telah menggunakan kerangka ini.","category":"产品更新","source":"NVIDIA Blog（RSS）","aggregationSource":"NVIDIA Blog（RSS）","pageTitle":"NVIDIA merilis kerangka simulasi fisika medis pertama yang dipercepat GPU secara open source - Berita AI Aioga","description":"NVIDIA mengumumkan membuka kode sumber kerangka Simulasi Fisika Medis, ini adalah kemampuan simulasi fisika medis yang dipercepat GPU pertama dalam Isaac for Healthcare. Kerangka i...","url":"https://www.aioga.com/id/news/cms3fbu4z00h6rond0qo6j75s/","contentTranslated":true,"sourceHash":"15c4701651f53a9e","translatedAt":"2026-07-27T17:50:03.190Z"},"th":{"title":"NVIDIA เปิดซอร์สเฟรมเวิร์กการจำลองฟิสิกส์การแพทย์ที่เร่งความเร็วด้วย GPU ครั้งแรก","summary":"NVIDIA ประกาศเปิดตัวกรอบการจำลองฟิสิกส์ทางการแพทย์แบบโอเพ่นซอร์ส ซึ่งเป็นความสามารถในการจำลองฟิสิกส์ทางการแพทย์ที่ใช้ GPU เร็วที่สุดครั้งแรกใน Isaac for Healthcare กรอบงานนี้สามารถรันสภาพแวดล้อมการฝึกหัดหุ่นยนต์แบบคู่ขนานได้ 8,192 ตัว ลดเวลาการฝึกจากมากกว่า 5 ชั่วโมงเหลือน้อยกว่า 2 นาที องค์กรอย่าง CMR Surgical และ Johnson & Johnson MedTech ได้เริ่มใช้กรอบงานนี้แล้ว","category":"产品更新","source":"NVIDIA Blog（RSS）","aggregationSource":"NVIDIA Blog（RSS）","pageTitle":"NVIDIA เปิดซอร์สเฟรมเวิร์กการจำลองฟิสิกส์การแพทย์ที่เร่งความเร็วด้วย GPU ครั้งแรก - ข่าว AI Aioga","description":"NVIDIA ประกาศเปิดตัวกรอบการจำลองฟิสิกส์ทางการแพทย์แบบโอเพ่นซอร์ส ซึ่งเป็นความสามารถในการจำลองฟิสิกส์ทางการแพทย์ที่ใช้ GPU เร็วที่สุดครั้งแรกใน Isaac for Healthcare กรอบงานนี้สามารถ...","url":"https://www.aioga.com/th/news/cms3fbu4z00h6rond0qo6j75s/","contentTranslated":true,"sourceHash":"15c4701651f53a9e","translatedAt":"2026-07-27T17:50:09.525Z"},"pl":{"title":"NVIDIA udostępnia pierwszy otwarty framework do symulacji fizyki medycznej przyspieszany przez GPU","summary":"NVIDIA ogłosiła udostępnienie w formie open source frameworku do symulacji fizyki medycznej, co stanowi pierwszą zdolność przyspieszonej przez GPU symulacji fizyki medycznej w Isaac for Healthcare. Framework ten może równolegle obsługiwać 8 192 środowisk treningowych dla robotów, skracając czas treningu z ponad 5 godzin do mniej niż 2 minut. Instytucje takie jak CMR Surgical i Johnson & Johnson MedTech już korzystają z tego frameworku.","category":"产品更新","source":"NVIDIA Blog（RSS）","aggregationSource":"NVIDIA Blog（RSS）","pageTitle":"NVIDIA udostępnia pierwszy otwarty framework do symulacji fizyki medycznej przyspieszany przez GPU - Aioga Wiadomości AI","description":"NVIDIA ogłosiła udostępnienie w formie open source frameworku do symulacji fizyki medycznej, co stanowi pierwszą zdolność przyspieszonej przez GPU symulacji fizyki medycznej w Isaa...","url":"https://www.aioga.com/pl/news/cms3fbu4z00h6rond0qo6j75s/","contentTranslated":true,"sourceHash":"15c4701651f53a9e","translatedAt":"2026-07-27T17:50:58.283Z"}}}}