Why some organizations with ML/AI use cases are moving away from the cloud?
Cloud computing isn’t going anywhere, but some companies using ML/AI are shifting to on-premise.
Cost is actually a big driver due to computationally intensive deep-learning models.
Model latency is a more commonly recognized reason to shift away from the cloud.
Also, data privacy and security do compel some companies to use on-prem systems.
This on-prem trend is growing among big box and grocery retailers that need large machine learning models for inventory predictions.
Major cloud providers state that the computing requirements for ML/AI would be expensive and cumbersome to be on-premise, but looks like the field is now maturing.
Even cloud giants are responding to the trend by subtly pushing their on-prem products for machine learning.
Every company first goes to the cloud these days, then they sort of try to move back a bit. As if they are trying to find the right balance.
#machinelearning #workloads #cloudcomputing #dataprivacy #latency #ml #ai *****
Ankit Rathi is a Cloud Data Technologist, published author & well-known speaker. His interest lies primarily in building end-to-end data/AI applications/products following best practices of Data Engineering and Architecture.
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