From InfoWorld: Machine learning, artificial intelligence—whatever the label, it’s fast becoming a way to reinvent enterprise IT mainstays and for the companies on top to stay on top.
Consider four of the most familiar names in technology: Intel, Google, IBM, and Microsoft are investing heavily in ML/AI with hardware designs intended to greatly accelerate the next generation of applications. Here’s how each of their plans stacks up.
The world’s best-known chipmaker recently introduced a new line of CPUs specifically aimed at ML applications: Knights Mill. It also mentioned plans to meld its CPUs with reprogrammable FPGA processors, a powerful but relatively underexploited technology for Intel.
After outfitting the Microsoft Azure cloud with specially designed FPGAs to add machine-learning-accelerated functions to its clusters, Microsoft is talking about allowing customers to program the devices directly to enable more powerful tools for machine learning in its cloud.
Google has been deeply invested in machine learning on the software side with frameworks like TensorFlow, but now provides a hardware complement—the Tensor Processing Unit—to accelerate specific machine learning functions.
IBM’s new machine learning toolset, PowerAI, runs a mix of IBM’s Power processors and Nvidia GPUs wired together using new proprietary hardware designed to tie CPUs and GPUs as closely as possible.
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