The MIT-Air Force AI Accelerator, will conduct fundamental research directed at rapid deployment of artificial intelligence (AI) innovations in operations, data management, cybersecurity, and vehicle safety.
North Carolina State researchers have developed a framework for deep neural networks that allows artificial intelligence (AI) systems to become better at performing previous tasks by learning from its prior actions.
While embedded vision is still an emerging technology, to date there are typically two main types of processors used in embedded systems – field programmable gate arrays (FPGAs) and graphics processing units (GPUs).
Texas A&M University researchers have been awarded a National Science Foundation (NSF) grant to research data mining to optimize decision making in the software brain.
The Open Eye Consortium announced the establishment of its multi-source agreement (MSA) outlining its mission to standardize advanced specifications for lower latency.
IIoT series, Part 1: Five ways to use cloud and IIoT to improve productivity: Your questions answered
Webcast presenters Alan Griffiths and Mohamed (Mo) Abuali, Ph.D. answered additional questions about topics such as augmented reality, 5G technology, and predictive analytics.
A technique developed by MIT researchers frees up more memory used by computers and mobile devices, allowing them to run faster and perform more tasks simultaneously.
MIT researchers have developer a flash-storage system designed to cut the energy and physical space required to store and manage data in data centers by half.
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Argonne National Laboratory’s exascale computer, Aurora, will launch in 2021 and will support machine learning and data science workloads alongside traditional modeling and simulation workloads.