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Photo by — @yucelmoran

Artificial Intelligence and the Semiconductor Market

A growth in semiconductors related to AI

Lately having started looking at artificial intelligence and hardware there has been a series of question that have come up. However one big question is regarding the network of resources that are required to build and maintain systems running artificial intelligence not only from a software perspective – additionally examining the supply chain.

  1. Storage will experience the highest growth, but semiconductor companies will capture most value in compute, memory, and networking.
  2. To avoid mistakes that limited value capture in the past, semiconductor companies must undertake a new value-creation strategy that focuses on enabling customized, end-to-end solutions for specific industries, or ‘microverticals.’”
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“Our research revealed that AI-related semiconductors will see growth of about 18 percent annually over the next few years — five times greater than the rate for semiconductors used in non-AI applications.”

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“Compute performance relies on central processing units (CPUs) and accelerators — graphics-processing units (GPUs), field programmable gate arrays (FPGAs), and application-specific integrated circuits (ASICs).”

They outline as well that the infrastructure of data centres may change.

“AI applications generate vast volumes of data — about 80 exabytes per year, which is expected to increase to 845 exabites by 2025.”

As I described earlier there is an interplay between software and hardware outside of the direct storage/compute.

Written by

AI Policy and Ethics at Student at University of Copenhagen MSc in Social Data Science. All views are my own.

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