NVIDIA DGX SuperPOD provides leadership-class AI infrastructure with agile, scalable performance for the most challenging AI training and inference workloads.
AI新药研发应用在当前主要集中在化学小分子药、生物类似药和生物制剂的从头研发上，多基于研发周期进行“单点式”突破而“全过程”（full stack）的应用较少。依照新药全生命周期，据从人工智能应用程序在新药研发各阶段应用发展的潜力，系统生物学、靶点识别、先导化合物确定、药物临床、药物重定向被认为是全球AI+新药...
Full-stack solution Rackspace AI Anywhere helps you accelerate deployment and time-to-value while reducing complexity and resource requirements. Provides pre-built tools, blueprints and frameworks Aids in the responsible and precise deployment of generative AI using your proprietary data Flexible deploymen...
Unlock smarter content creation, deeper insights & automation with Generative AI solutions powered by NVIDIA’s full-stack AI platform.
Orin DLA 功能的这种有效利用对于将 RetinaNet 的性能和能效提高 50% 以上(在同一硬件上不到一年的时间)至关重要,从而实现 NVIDIA 不断提高 Jetson AGX Orin 软件性能的承诺。看见Delivering Server-Class Performance at the Edge with NVIDIA Jetson Orin了解更多信息。
Aspect Biosystems是一家率先开发生物打印组织疗法的生物技术公司,通过应用其“全堆叠组织治疗平台(full-stack tissue therapeutic platform)”来开发下一代细胞疗法。该平台将公司专有的生物打印技术、治疗细胞、生物材料和计算组织设计相结合,以构建同种异体组织疗法。设计的组织具有生物功能和免疫保护作用,适合手术和植入...
usingSystem;usingSystem.Collections.Generic;//////用位表示的世界状态///publicclassGoapWorldState:IAStarNode<GoapWorldState>,IComparable<GoapWorldState>,IEquatable<GoapWorldState> {publicconstintMAXATOMS =64;//存储的状态数上限,由于用long类型存储,最多就是64(long类型为64位整数)publiclongValues//世界...
AI-based full stack observability platform. Founded in 2022 by Laduram Vishnoi, Middleware has 40 employees based in 133 Kearny St, San Francisco, CA 94108, USA.
Full-stack machine learning development/deployment platform: Azure Machine Learning services for experiment tracking, distributed training, curated containers, MLOps, Responsible AI tools and model hosting for inference. We also offer PyTorch Enterprise for Azure, which includes long-term support, prioritiz...
See Delivering Server-Class Performance at the Edge with NVIDIA Jetson Orin to learn more. Figure 6. Performance comparison of Jetson AGX Orin in MLPerf Inference v3.0 compared to v2.0 for ResNet-50, BERT, 3D U-Net, and RNN-T, and v2.1 for RetinaNet Performance increase der...