Edge computing, a process in which computing happens on local servers and devices “on the edge” of the network instead of on distant cloud data centers. Despite its growing popularity and accessibility, is edge computing an enduring solution for efficient and accurate data processing? Read some of the pros and cons.
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Noodle.ai’s FlowOps uses Explainable AI to streamline production, Supply Chains
The FlowOps platform unveiled this week by supply chain specialist Noodle.ai leverages capabilities such as explainable AI to address multi-trillion-dollar losses annually attributed to product defects, unscheduled manufacturing downtime and excess inventory often associated surge demand.
Read MoreNvidia, VMware partner on enterprise AI via vSphere
Nvidia and VMware are collaborating to combine the virtualization specialist’s installed base and its updated vSphere platform as the foundation of scalable infrastructure based on Nvdia’s AI software suite.
Read MoreUniversity of Pisa leans into the I/O challenge AI applications create
At a time when workloads that employ machine and deep learning algorithms are being built and deployed more frequently, organizations need to optimize I/O throughput in a way that enables those workloads to cost-effectively share the expensive GPU resources used to train AI models. Case in point: the University of Pisa, which has been steadily expanding the number of GPUs it makes accessible to AI researchers in a green datacenter optimized for high-performance computing (HPC) applications.
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