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How to improve cloud-based generative AI performance

It’s Monday. You come into the office only to be met with a dozen emails from your system development teammates requesting to speak with you right away. It seems that the generative AI-enabled inventory management system you launched a week ago is frustrating its new users. It’s taking minutes, not seconds to respond. Shipments are now running late. Customers are hanging up on your service reps because they are taking too long to answer customer questions. Website sales are down by 20% due to performance lags. Whoops. You have a performance problem.

But you did everything right. You’re using only GPUs for processing training and inferences; you did all recommended performance testing; you have over-provisioned the memory space, and you are only using the fastest storage with the best I/O performance. Indeed, your cloud bill is greater than $100K a month. How can performance be failing?

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