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.
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⏯ Adapt AI to your Existing Architecture @ Global Summit 2024
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⏯ Big Data, AI and ChatGPT in Healthcare @ Global Summit 2024
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⏯ Human Centered AI: Shaping a Just and Ethical Future in Health Technology @ Global Summit 2024
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Our project reimagines learning for all students, with a focus on accessibility and interactive experiences. Built with the goal of making education engaging and inclusive, the tool is designed to support students of all abilities in learning complex material in an intuitive way.
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This educational app transforms lesson presentations into interactive study sessions:
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⏯ How to Fail with AI (and how to succeed!) @ Global Summit 2024
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⏯ Prompt before the prompt - third step of GenAI model training
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⏯ Securing AI Implementations - Moving from Experimentation to Production @ Global Summit 2024
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.
Generative AI is artificial intelligence capable of generating text, images and other types of content. What makes it a fantastic technology is that it democratizes AI, anyone can use it with as little as a text prompt, a sentence written in a natural language.
how large language m
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We continue with this series of articles on LLM and RAG applications and in this article we will discuss the red boxed part of the following diagram:
In the process of creating a RAG application, choosing an LLM model that is appropriate to your needs (trained in the corresponding subject, costs, speed, etc.) is as important as having a clear understanding of the context you want to provide. Let's start by defining the term to be clear about what we mean by context.
Context refers to additional information obtained from an external source, such as a database or search e
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Watch this video to learn how InterSystems partner Mirus uses InterSystems IRIS to deliver clean data from multiple systems and feed a robust AI model that ensures that providers receive full funding for each resident while reducing administrative burden:
⏯ Using AI to Automate and Improve Resident Funding in Nursing Homes @ Global Summit 2024
hi everyone,
I'm trying to make some use of AI to help with coding. To achieve this I've moved to VS Code linking to a cache instance, and installed the "Cody" extension from Sourcegraph that talks to Claude Sonnet.
In theory Cody can view, and send to the AI, the file I'm currently editing. However, it does not seem to "see" Cache server items, and only works for stuff in ordinary files that I have open. Is this an issue with "isfs" ("InterSystems File Service" that implements the "filesystem provider API" )? Is anyone else using Cody or any other AI extension successfully?
Thanks,
Mike
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Want to dive deeper into the concepts of vector searches and embeddings? Learn from an InterSystems expert:
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What components and libraries can you add to your retrieval-augmented generation (RAG) applications? Find out in this video:
Identifying Useful Components for Your Generative AI Application
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⏯ InterSystems IRIS Vector Search and the Python Ecosystem @ Global Summit 2024
In today's data landscape, businesses encounter a number of different challenges. One of them is to do analytics on top of unified and harmonized data layer available to all the consumers. A layer that can deliver the same answers to the same questions irrelative to the dialect or tool being used. InterSystems IRIS Data Platform answers that with and add-on of Adaptive Analytics that can deliver this unified semantic layer. There are a lot of articles in DevCommunity about using it via BI tools. This article will cover the part of how to consume it with AI and also how to put some insights bac
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Curious how a retrieval-augmented generation (RAG) application works? Take a look at this demonstration:
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Ready to create a retrieval-augmented generation (RAG) architecture for your next GenAI application? See how to get started:
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We’re thrilled to invite you to an exciting LinkedIn Live session dedicated to the most common myths and misconceptions surrounding AI!
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Are you building generative AI applications? See how a retrieval-augmented generation (RAG) architecture can help:
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How can you get your data ready for generative AI applications? Get some key tips from an InterSystems expert:
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Are you using generative AI tools for development? Let InterSystems principles be your guiding star! 🌟 Learn about the company's approach:
Using Generative AI Responsibly
I received some really excellent feedback from a community member on my submission to the Python 2024 contest. I hope its okay if I repost it here:
you build a container more than 5 times the size of pure IRIS
and this takes time
container start is also slow but completes
backend is accessible as described
a production is hanging around
frontend reacts
I fail to understand what is intended to show
the explanation is meant for experts other than me
The submission is here: https://openexchange.intersystems.com/package/IRIS-RAG-App
I really appreciate this feedback, not the least
In the previous article we presented the d[IA]gnosis application developed to support the coding of diagnoses in ICD-10. In this article we will see how InterSystems IRIS for Health provides us with the necessary tools for the generation of vectors from the ICD-10 code list using a pre-trained language model, its storage and the subsequent search for similarities on all these generated vectors.
One of the main features that have emerged with the development of AI models is what we know as RAG (Retrieval-Augmented Generation) that allows us to improve the results of LLM models
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