Hich Can Result In High Training Costs These Factors Make The Process Challenging And Time Consuming For System Integrators Developers Ai Model Deployment Also Be Difficult When Have Multiple Remote Edge Devices Different Locations Challenges Of Include Optimizing Models Inference To Run Efficiently On News Today : Breaking News, Live Updates & Top Stories | Vimarsana

NEW TAIPEI CITY, Taiwan, Sept. 22, 2022 /PRNewswire/ Aetina, a leading edge AI solution provider, introduced its end-to-end AI management solution in an NVIDIA GTC on-demand session this week. The solution helps global AI partners and clients of Aetina successfully adopt edge AI using NVIDIA AI development and deployment tools, as well as Aetina's NVIDIA AI-powered training and inference platforms. In the session, Jeremy Pan, AI Solutions Product Manager at Aetina, deep dived into Aetina's solution, and shared an impactful application case of AI-powered automatic optical inspection (AOI) in a client's factory in Yilan, Taiwan. Challenges of Edge AI Adoption To adopt edge AI, system integrators and developers need to train AI models and deploy them on edge devices. The AI model training process involves collecting and labeling large amounts of data using high-performance computing platforms, which can result in high training costs. These factors make the training process ch ....

Yilan Xian , Jeremy Pan , Ai Solutions Product , Aetina Corporation , Product Manager , Application Case , New Taipei City , Sept 22 , 022 Prnewswire Aetina , A Leading Edge Ai Solution Provider , Ntroduced Its End To Ai Management Solution In An Nvidia Gtc On Demand Session This Week The Helps Global Partners And Clients Of Aetina Successfully Adopt Edge Using Development Deployment Tools , S Well As Aetina 39s Nvidia Ai Powered Training And Inference Platforms In The Session , Jeremy Pan , I Solutions Product Manager At Aetina , Eep Dived Into Aetina 39s Solution , Nd Shared An Impactful Application Case Of Ai Powered Automatic Optical Inspection Aoi Ina Client 39s Factory In Yilan , Aiwan Challenges Of Edge Ai Adoption To Adopt , Ystem Integrators And Developers Need To Train Ai Models Deploy Them On Edge Devices The Model Training Process Involves Collecting Labeling Large Amounts Of Data Using High Performance Computing Platforms , Hich Can Result In High Training Costs These Factors Make The Process Challenging And Time Consuming For System Integrators Developers Ai Model Deployment Also Be Difficult When Have Multiple Remote Edge Devices Different Locations Challenges Of Include Optimizing Models Inference To Run Efficiently On , Ong Deployment Processes , Ifficulties Of Team Communication And Collaboration , Igh Follow Up Monitoring Costs Caused By Large Number Of Ai Models , Security Issues , Nd High Costs End To Ai Management Solution Aetina Provides An Help Its Partners And Clients Develop Deploy Applications For The Edge Consists Of 39s Nvidia Certified Computing Platforms Model Development Deployment Tools These Include Fleet Command , Nd The Nvidia Ai Enterprise Software Suite , Hich Provides Enterprise Support For The Nvidia Tao Toolkit And Tritoninference Server With Aetina 39s Certified Edge Computing Platforms Other Tools ,