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.
Do you resonate with this - A capability and impact of a technology being truly discovered when it's packaged in a right way to it's audience. Finest example would be, how the Generative AI took off when ChatGPT was put in the public for easy access and not when Transformers/RAG's capabilities were identified. At least a much higher usage came in, when the audience were empowered to explore the possibilities.
Several years ago everyone got mad about BigData – nobody knew when smallish data will become BIGDATA, but all knows that it’s trendy and the way to go.
This series of articles would cover Python Gateway for InterSystems Data Platforms. Leverage modern AI/ML tools and execute Python code and more from InterSystems IRIS. This project brings you the power of Python right into your InterSystems IRIS environment:
As you have seen in the latest community publications, InterSystems IRIS has included since version 2024.1 the possibility of including vector data types in its database and based on this type of data vector searches have been implemented. Well, these new features reminded me of the article I published a while ago that was based on facial recognition using Embedded Python.
Yet another example of applying LangChain to give some inspiration for new community Grand Prix contest.
I was initially looking to build a chain to achieve dynamic search of html of documentation site, but in the end it was simpler to borg the static PDFs instead.
In a fast-paced clinical environment, where quick decision-making is crucial, the lack of streamlined document storage and access systems poses several obstacles. While storage solutions for documents exist (e.g, FHIR), accessing and effectively searching for specific patient data within those documents meaningfully can be a significant challenge.
I created this application considering how to convert images such as prescription forms into FHIR messages
It recognizes the text in the image through OCR technology and extracts it, which is then transformed into fhir messages through AI (LLA language model).
Finally, sending the message to the fhir server of IntereSystems can verify whether the message meets the fhir requirements. If approved, it can be viewed on the select page.
Diabetes can be discovered from some parameters well known to the medical community. In this way, in order to help the medical community and computerized systems, especially AI, the National Institute of Diabetes and Digestive and Kidney Diseases published a very useful dataset for training ML algorithms in the detection/prediction of diabetes. This publication can be found on the largest and best known data repository for ML, Kaggle at https://www.kaggle.com/datasets/mathchi/diabetes-data-set.
In this article, I will introduce my application IRIS-GenLab.
IRIS-GenLab is a generative AI Application that leverages the functionality of Flask web framework, SQLALchemy ORM, and InterSystems IRIS to demonstrate Machine Learning, LLM, NLP, Generative AI API, Google AI LLM, Flan-T5-XXL model, Flask Login and OpenAI ChatGPT use cases.
A robot is not expected to be either huge or humanoid, or even material (in disagreement with Wikipedia, although the latter softens the initial definition in one paragraph and admits virtual form of a robot). A robot is an automate, from an algorithmic viewpoint, an automate for autonomous (algorithmic) execution of concrete tasks. A light detector that triggers street lights at night is a robot. An email software separating e-mails into “external” and “internal” is also a robot. Artificial intelligence (in an applied and narrow sense, Wikipedia interpreting it differently again) is algorithms for extracting dependencies from data. It will not execute any tasks on its own, for that one would need to implement it as concrete analytic processes (input data, plus models, plus output data, plus process control). The analytic process acting as an “artificial intelligence carrier” can be launched by a human or by a robot. It can be stopped by either of the two as well. And managed by any of them too.
We have more exciting news! The new InterSystems online programming contest dedicated to Generative AI, Vector Search and Machine Learning is starting very soon!
InterSystems Innovation Acceleration Team invites you to take part in the GenAI Crowdsourcing Mini-Contest.
GenAI is a powerful and complex technology. Today, we invite you to become an innovator and think big about the problems it might help solve in the future.
We're continuing to improve and teach our Developer Community AI, and in this iteration, we've added descriptions of Open Exchange Applications to the knowledge base!
This new feature will allow DC AI to search app descriptions to answer your questions. This will give you better answers that require programming, not just general information.
To add this knowledge to your search, just tick the checkbox Open Exchange Applications:
Hi all. Today we are going to upload a ML model into IRIS Manager and test it.
Note: I have done the following on Ubuntu 18.04, Apache Zeppelin 0.8.0, Python 3.6.5.
Introduction
These days many available different tools for Data Mining enable you to develop predictive models and analyze the data you have with unprecedented ease. InterSystems IRIS Data Platform provide a stable foundation for your big data and fast data applications, providing interoperability with modern DataMining tools.
As you may know, our Developer Community AI has been out for over a month now 🎉 We hope you were curious enough to give it a try 😁 If you haven't yet, please do! Anyway, since it's still in beta, we're very interested in learning what you think about it, and we look forward to hearing your thoughts and experiences.
Since we value your time and effort, we will give away a cute prize to a random member of the Community who shares how DC AI helped you. To participate in this sweepstakes, you have to follow the guidelines:
Here is another quick note before we move on to GPT-4 assisted automation journey. Below are some "little" helps ChatGPT had already been offering, here and there, during daily works.
And what could be the perceived gaps, risks and traps to LLMs assisted automation, if you happen to explore this path too. I'd also love to hear anyone's use cases and experiences on this front too.
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.
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