Artificial Intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions) and self-correction.
As said in the previous article about the iris-fhir-generative-ai experiment, the project logs all events for analysis. Here we are going to discuss two types of analysis covered by analytics embedded in the project:
ChatIRIS Health Coach, a GPT-4 based agent that leverages the Health Belief Model (Hochbaum, Rosenstock, & Kegels, 1952) as a psychological framework to craft empathetic replies.
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Episode 17 of Data Points features a roundtable conversation with Carmen Logue, Benjamin De Boe, and Thomas Dyar about the Analytics & AI area of the InterSystems technology stack. Learn from these product experts about the various technologies and partnerships that exist within the Analytics & AI space at InterSystems, how some customers use these tools, and what might be coming in the future.
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In the previous article, we saw different modules in IRIS AI Studio and how it could help explore GenAI capabilities out of IRIS DB seamlessly, even for a non-technical stakeholder. In this article, we will deep dive into "Connectors" module, the one that enables users to seamlessly load data from local or cloud sources (AWS S3, Airtable, Azure Blob) into IRIS DB as vector embeddings, by also configuring embedding settings like model and dimensions.
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In our latest episode of Data Points, I had a conversation with @Thomas Dyarabout AI Link, which helps bridge the gap between data scientists and business analysts. Our conversation talks about how AI Link fits with IntegratedML and Adaptive Analytics, as well, as what new features are on the horizon for IntegratedML. Take a listen!
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Generative artificial intelligence is artificial intelligence capable of generating text, images or other data using generative models, often in response to prompts. Generative AI models learn the patterns and structure of their input training data and then generate new data that has similar characteristics.
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Looking to get started with generative AI? Try two brand-new learning paths. In Getting Started with Generative AI (2h 45m), learn the basics of interacting with GenAI. Then, try Developing Generative AI Applications (2h) to start developing your own GenAI application. Plus, earn badges for completing each path!
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.
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The introduction of InterSystems' "Vector Search" marks a paradigm shift in data processing. This cutting-edge technology employs an embedding model to transform unstructured data, such as text, into structured vectors, resulting in significantly enhanced search capabilities. Inspired by this breakthrough, we've developed a specialized search engine tailored to companies.
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:
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In the previous article, we saw in detail about Connectors, that let user upload their file and get it converted into embeddings and store it to IRIS DB. In this article, we'll explore different retrieval options that IRIS AI Studio offers - Semantic Search, Chat, Recommender and Similarity.
ChatIRIS Health Coach, a GPT-4 based agent that leverages the Health Belief Model as a psychological framework to craft empathetic replies. This article elaborates on the backend architecture and its components, focusing on how InterSystems IRIS supports the system's functionality.
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.
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