When to Host AI Databases in the Cloud
Healthcare organizations’ plans for generative AI will determine how they should prepare their infrastructure for the future of this technology. Haney says most users want to communicate with their data for retrieval or analytical purposes.
“Chatting with your data doesn’t require a new data store. You don’t have to build a huge data lake or warehouse,” he says. “If you have patient data, then we add another model that can create the query in SQL, do the query and pull the data back. Then you can ask it questions, using that data as part of your prompt, and you can ‘talk’ with your data.”
Partners such as CDW can give healthcare organizations this functionality quickly and inexpensively by creating a retrieval-augmented generation database for health systems. When asked a simple question, it can return two or three top answers. Often, these solutions don’t require the cloud.
“If you’re going to do 20 queries per second, for example, you probably could do that on-premises,” Haney says. “If you’re going to do 200 queries or, if you’re a company the size of CDW and you’re building an HR bot, 500 queries per second, you want to do that with resources that are scalable. That’s where the cloud comes in.”
The size of the organization and the types of AI use cases it plans to implement will determine whether a health system should consider hosting a database on-premises or use cloud-based resources.
DIVE DEEPER: When is the cloud right for organizations deploying artificial intelligence?
“With a fine-tuned model, you need heavy GPU resources because now you’re embedding that information into the model itself,” Haney says. “We do most of that work in in the cloud, where we’re able to rent a GPU or a TPU [tensor processing unit], and it’s a lot less expensive.”
“We’re also working with a lot with hospitals on the manual processes they do today. You can simply walk into the room, attach to all the automatic blood pressure cuffs and these types of things, and produce a diagnosis right there on the doctor’s device,” adds Haney. “What does your past 12 or 24 hours look like? The thing to think about with AI, especially generative AI, is that it’s another tool. But chaining a lot of these tools together — your databases, your queries and lookups, a lot of the video — provides you with a really intelligent solution.”
So, when it comes to determining how you’ll prepare your cloud infrastructure for AI, think first about how you want to use AI, how you want to use your data and what that will require in your organization. Working with an experienced partner can help you answer these questions and more to prepare your healthcare organization’s digital infrastructure for whatever comes next.
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