Scaling AI Requires Hardware and Software that Work Well Together

IDC has identified more than a dozen additional AI use cases that are being developed in such industries as transportation, manufacturing, education, and healthcare. These use cases leverage a variety of advanced software platforms for AI such as conversational AI, predictive analytics, text analytics, voice and speech analytics, and image and video analytics.

AI parses vast amounts of data and requires powerful parallel processing capabilities based on many more cores than CPUs can deliver. Parallel processing is best achieved with clustered servers that have multithreaded CPUs combined with multicore co-processors such as graphics processing units (GPUs), fast interconnects, large amounts of memory, and advanced I/O capabilities.

For IT organizations, the hardware and software requirements can present a major challenge if they choose to combine and optimize the many components themselves. IT will achieve better results and waste a lot less time with a fully supported cooptimized hardware-software solution for AI.

 Software Development
IBM

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