Watch this video to learn how to programmatically manage task schedules using InterSystems IRIS, including creation, editing, and deleting a user-defined task:
What are the advantages of using multiple namespaces for your code? Learn some of the benefits in this discussion with @Derek Robinson, Senior Online Course Developer, and @Scott Clark, Implementation Specialist:
Watch this video to discover an analytical approach to InterSystems IRIS encryption and how it interacts with storage compression and deduplication compared with storage-level encryption:
Watch this video to learn about the PainChek artificial intelligence technology, which assesses patient pain at the hospital bedside, leverages InterSystems IRIS interoperability to connect to third-party electronic medical record systems:
🗣 Presenter:@Mark Bolinsky, Principal Technology Architect, InterSystems
This demo was prepared for one of our past online developer roundtables. We encourage you to ask your specific questions about this topic in the comments section, and we will invite our experts to answer them!
Watch this video to learn how UC Davis Health is implementing a centralized operations-monitoring and alerting framework to handle notifications across its InterSystems IRIS infrastructure using ServiceNow, an IT service management platform:
Watch this video to learn how to use HL7® FHIR® Shorthand (a domain-specific, human-readable language for defining profiles, extensions, and other FHIR artifacts) to more efficiently create a FHIR Implementation Guide:
Watch this video to get an overview of how UC Davis Health uses HealthShare and Smart on FHIR to integrate genomics results into medical records as interactive discrete result pages:
This is a detailed, candid walkthrough of the IRIS AI Studio platform. I speak out loud on my thoughts while trying different examples, some of which fail to deliver expected results - which I believe is a need for such a platform to explore different models, configurations and limitations. This will be helpful if you're interested in how to build 'Chat with PDF' or data recommendation systems using IRIS DB and LLM models.
Here is a brief walkthrough on the capabilities of IRIS AI Studio platform. It covers one complete flow from loading data into IRIS DB as vector embeddings and retrieving information through 4 different channels (search, chat, recommender and similarity). In the latest release, added docker support for local installation and live version to explore.
The basic idea is to use Vectors in the mathematical sense. I used geographic coordinates. These are of course only 2-dimensional but much easier to follow as vectors in text analysis with >200 dimensions.
Building my tech. example provided me with a bunch of findings htt I want to share. The first vectors I touched appeared with text analysis and more than 200 dimensions. I have to confess that I feel well with Einstein's 4 dimensional world. 7 to 15 dimensions populating the String Theory are somewhat across the border. But 200 and more is definitely far beyond my mathematical horizon.
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