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AI/ML Brain Food – Part 2: What’s on the menu?

Welcome to AI/ML Brain Food Part 2 – What’s on the menu. This second article follows up on the previous part, AI/ML Brain Food – Part 1: Where to Start? 

We will take the foundation from before and layer on top a question – “What tools are available to help me prepare for AI/ML workloads?

Today, we’re focusing on getting your on-prem private/hybrid cloud ready for AI/ML type workloads. Most of this logic could be applied to other HPC type workloads too and some of this might be worth checking out as just a good idea in general!

Performance, Quality and Control are the name of the game here. The performance and the quality are essential for the AI/ML output to become useful. Control is going to allow you to scale effectively, keep costs at bay and make sure the right guardrails are in place from a compliance perspective. Connectivity also becomes very important as you distribute the workload across different clouds/regions etc. As with any workload, you want it to work in production, not just on an isolated island, but connected to your existing apps and databases. I still need to secure the workloads, protect them and also provide them with resources. The major difference is that the amount of data will explode, because as we remember from the previous post, data is key to AI/ML

This is where PrepOps comes in….

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