On-Premise or Cloud - Where Should You Host Your AI Applications?
The more reliant a task is on a large and private dataset, the more likely it is that a workflow application will be dominant instead of a model. The best software companies function as a system of record, a repository for the most important data (customer IDs, product analytics, or credit card numbers), and they’ll be able to offer superior produc
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A solution is to self-host an open-sourced or custom fine-tuned LLM. Opting for a self-hosted model can reduce costs dramatically - but with additional development time, maintenance overhead, and possible performance implications. Considering self-hosted solutions requires weighing these different trade-offs carefully.
Developing Rapidly with Generative AI
For example, an application may use Microsoft Azure for storage, AWS for compute, IBM Watson for deep learning, and Google Cloud for image recognition.