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electronics360.globalspec
10 小时
Aetina pursues edge AI enhancements with Super Mode support for NVIDIA Jetson Orin NX and ...
Aetina, a provider of edge artificial intelligence (AI) solutions, announces its comprehensive support for Super Mode, a ...
Electronics Weekly
8 天
Dev board for Nvidia Jetson Orin NX
Aaeon has released its first development kit for Nvidia's Jetson Orin NX AI system-on-module. Boxer-8654AI-kit is a carrier ...
新浪网
27 天
英伟达将推紧凑型计算机Jetson Thor,专为人形机器人打造,此前已 ...
据媒体报道,其将于 2025 年上半年推出最新一代紧凑型计算机——Jetson Thor。该计算机专为人形机器人打造,旨在为人形机器人提供 AI 训练工具。
中時新聞網
12 天
《电周边》宜鼎旗下安提导入Super Mode技术 推升机器人、AI效能
宜鼎(5289)集团子公司边缘AI解决方案品牌厂安提国际(Aetina)周四宣布推出的Super Mode功能,全面支援NVIDIA Jetson Orin NX及Jetson Orin Nano模组。这项技术可透过本月份所发表的NVIDIA JetPack 6.2软体开发套件启 ...
5 天
Unleash 100 TOPS AI Power : AAEON’s BOXER-8654AI-KIT NVIDIA Jetson Orin NX
AAEON’s BOXER-8654AI-KIT, powered by the NVIDIA Jetson Orin NX module, delivers up to 100 TOPS of AI performance, ideal for ...
来自MSN
1 个月
英伟达发Jetson Orin Nano Super开发套件 性能再升级
此外,英伟达表示使用当前一代产品的用户,在安装新的软件后同样可以获得相应的性能提升,比如Jetson Orin NX 16GB从100 TOPS跃升至157 TOPS,Jetson Orin NX ...
14 天
Frore Systems 与 NVIDIA 齐头并进 推动 AI 性能提升
美国加州圣何塞——2024 年 12 月 23 日:NVIDIA 全新 25 瓦的“小型 Jetson Nano”——Jetson Orin Nano Super,具备每秒 67 万亿次运算(TOPS)的 AI 性能。然 ...
来自MSN
20 天
NVIDIA Jetson Orin Nano Super Developer Kit发布
本次更新,包含现有的Jetson Orin NX和Orin Nano系列模组设备也可以通过软件更新的方式获AI性能的提升。 Jetson自诞生以来,便是定位于AI边缘计算应用 ...
Manufacturing
8 天
Aetina Announces Support for NVIDIA's Super Mode
Edge AI solutions provider Aetina announced its comprehensive support for Super Mode, a feature introduced in the latest ...
Digi Times
12 天
Aetina partners with Nvidia and Qualcomm to enhance edge AI applications
Aetina, a subsidiary of Innodisk, has announced comprehensive support for the super mode feature introduced by Nvidia's ...
Taiwan News
12 天
Aetina Embarks on Revolutionary Edge AI Enhancements with Super Mode Support for NVIDIA ...
Super Mode transforms the operational capabilities of the Jetson Orin platforms by enhancing their processing performance and efficiency, making them ideal for demanding AI applications at the edge.
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