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Composable Architecture For Uneven A.I. Workloads

Posted on
April 17, 2019

What is the value of using Composable Architecture for uneven A.I. Workloads? We've been training machines to think for us for decades, and we're just at the beginning. Today we've got Alexa, and Siri and other services that are delivering real-time services. All of this are instantiations of A.I..

When consider what else is happening w/ machine learning and w/ deep learning you start to see an evolution in the IT space...really in the world. That evolution is driving a increased demand for computational resources, and more importantly on-demand computational resources that dynamically shift based on usage requirements. And with the advances in artificial intelligence, why should an IT staffer have to manually configure resources to adjust if - for example - utilization rates go above 84 percent?

That's silly. Machines now understand this shift needs to happen - automatically. That's that's the idea behind Liqid composable infrastructure. It's IT nirvana if you will. Being able to automated dynamic workloads across the datacenter regardless of industry vertical.

https://www.youtube.com/channel/UCh13Y_63zKTz0c9rzEFHbXg/videos

#ComposableInfrastructure #AIDatacenter #ArtificialIntelligenceDatacenter

Posted on
April 17, 2019
in
Artificial Intelligence
category

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