Generative AI refers to algorithms and models in artificial intelligence that are capable of generating new data or content that is similar to existing data. These models are trained on large datasets and learn to generate new examples that mimic the patterns and characteristics of the original data.
While working with the FHIR to OMOP Service, I've seen good FHIR synthetic data being created using commercial LLM's etc, custom tailored for ConditionOnset with the typical amazement on return, but witnessed some questionable trust first hand on a call. This approach also falls short generating gigantic payloads so I can go back to my interests on the backend and ensure smooth data transition.
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We're working on new capabilities to help you build Agents and AI applications faster with InterSystems IRIS. In order to better understand which entry points and development methodologies would help you most, we've created this brief survey: Building AI solutions with InterSystems IRIS.
Filling it in should not take much more than 5 minutes, and your feedback on this exciting topic will help us fine tune our designs and prioritize the right features.
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