Adrian JohnsonTLDR:
- NTT and Red Hat, along with NVIDIA and Fujitsu, have developed a solution for AI analysis at the edge.
- The solution reduces power consumption and latency while enabling real-time AI data analysis.
NTT, Red Hat, NVIDIA, and Fujitsu have collaborated on a cutting-edge solution that leverages the Innovative Optical and Wireless Network (IOWN) initiative to enhance real-time artificial intelligence (AI) data analysis at the edge. This solution, built on Red Hat OpenShift and recognized by the IOWN Global Forum’s Proof of Concept, aims to address the growing demand for AI inferencing by reducing power consumption and latency.
Key elements of the solution include NTT’s accelerated data pipeline for AI, which utilizes RDMA over APN to efficiently process sensor data at the edge. Red Hat OpenShift provides container orchestration technology for flexible workload operation, contributing to lower power consumption and reduced latency for real-time AI analysis. The proof of concept demonstrated a 60% reduction in latency and a 40% decrease in power consumption compared to conventional AI inference workloads.
This solution paves the way for sustainable and innovative AI-enabled technologies, offering benefits such as reduced data collection overhead, enhanced data sharing between locations, and the utilization of locally available energy sources. With the collaboration of key technology partners, this solution represents a significant step towards sustainable AI innovation for businesses globally.
Full Article:
NTT, Red Hat, NVIDIA, and Fujitsu have joined forces to develop a state-of-the-art solution for AI analysis at the edge, leveraging the IOWN initiative to enhance real-time AI data analysis while reducing power consumption and latency. This collaborative effort has resulted in a solution that has been recognized by the IOWN Global Forum for its real-world viability and use cases.
The solution incorporates NTT’s accelerated data pipeline for AI, which uses RDMA over APN to efficiently collect and process sensor data at the edge. Red Hat OpenShift’s container orchestration technology allows for flexible workload operation, contributing to lower power consumption and reduced latency for real-time AI analysis at the edge.
The proof of concept testing demonstrated significant improvements, with a 60% reduction in latency and a 40% decrease in power consumption for AI analysis at the edge. This innovative solution sets the stage for sustainable AI-enabled technologies, offering benefits such as reduced data collection overhead, enhanced data sharing between locations, and the use of locally available energy sources.
Overall, this collaboration between NTT, Red Hat, NVIDIA, and Fujitsu represents a significant advancement in AI analysis capabilities at the edge, providing businesses with a sustainable and innovative solution for real-time AI data analysis.
