Trends Report

AI Deep Learning Workloads Demand A New Approach To Infrastructure

GPUs Dominate Now, But A Broader Landscape Of AI Chips And Systems Is Evolving Quickly

May 4th, 2018
Mike Gualtieri, VP, Principal Analyst
Mike Gualtieri VP, Principal Analyst
Christopher Voce, null
Christopher Voce
With contributors:
Srividya Sridharan , Michele Goetz , Renee Taylor-Huot

Summary

One breakthrough of AI is deep learning: a branch of machine learning that can uncannily identify objects in images, recognize voices, and create other predictive models by analyzing enterprise data. Deep learning can use regular CPUs, but for serious enterprise projects, data science teams must use AI chips such as GPUs that can handle massively parallel workloads to train and retrain models on large data sets more quickly. This report helps I&O professionals understand their AI infrastructure options — chips, systems, and cloud — to execute on deep learning.

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