Considering new business interest in applying Generative-AI to local commercially sensitive private data and information, without exposure to public clouds. Like a match needs the energy of striking to ignite, the Tech lead new "activation energy" challenge is to reveal how investing in GPU hardware could support novel competitive capabilities. The capability can reveal the use-cases that provide new value and savings.
Sharpening this axe begins with a functional protocol for running LLMs on a local laptop.
Killer presentations are essential for opening doors, doing business and delighting customers. These types of presentations move away from the traditional and tiring topics and portions of texts, or even pictures of happy people to get closer to the interests of their audience.The best presentations materialize what customers are looking for into something they can see working. Instead of promises, examples in execution and the ability to be very close to what you want to do.
We have a yummy dataset with recipes written by multiple Reddit users, however most of the information is free text as the title or description of a post. Let's find out how we can very easily load the dataset, extract some features and analyze it using features from OpenAI large language model within Embedded Python and the Langchain framework.
In this article, we will explore the use of parameters, formulas and labels in Logi Report Designer (formerly Logi JReport Designer). What are they for and how to create them?
Using the basic functionality of InterSystems Reports Designer, parameters, formulas and labels, you can significantly improve the detail and information content of the generated report. In addition, these tools allow you to automate some of the processes, which greatly speeds up and facilitates the creation of reports.
Have you ever been editing files in VS Code, but needed to check a global value or run a few ObjectScript commands? Now you can, with no setup required! If you have vscode-objectscript extension version 2.10.0 or later and are connected to InterSystems IRIS 2023.2 or later, you can now open a terminal connection to your server, regardless of where it's located.
In today's digital age, effective data management and accurate information analysis are becoming essential for successful enterprise operations. InterSystems IRIS Data Platform offers two critical tools, ARCHITECT and ANALYZER, developed to deliver convenient data management.
We all know that having a set of proper test data before deploying an application to production is crucial for ensuring its reliability and performance. It allows to simulate real-world scenarios and identify potential issues or bugs before they impact end-users. Moreover, testing with representative data sets allows to optimize performance, identify bottlenecks, and fine-tune algorithms or processes as needed. Ultimately, having a comprehensive set of test data helps to deliver a higher quality product, reducing the likelihood of post-production issues and enhancing the overall user experience.
In this article, let's look at how one can use generative AI, namely Gemini by Google, to generate (hopefully) meaningful data for the properties of multiple objects. To do this, I will use the RESTful service to generate data in a JSON format and then use the received data to create objects.
In the ever-evolving landscape of data science and machine learning, having the right tools at your disposal can make all the difference. In this article, we want to shine a spotlight on two essential Python libraries that have become indispensable for data scientists and machine learning practitioners alike: Matplotlib and scikit-learn.
To create a user-defined error you need to prepare the XML that describes the error code and corresponding message that you want to use as a user-defined error.
So far, we have covered how to use ObjectScript to manage users, roles, resources, and applications. There are a few other classes in this package that work similarly to the ones mentioned above. However, these four classes are the ones everyone will have to use to manage their application security.
I though this is a pretty cool way of installing webterminal in an environment where I had Management Portal / Visual code access, but I had no terminal access.
zpm was already present. otherwise you could add it in the same class.
We know that you love to brag about your achievements! Еo make it even easier for you, we've implemented the data exchange with Credly: all InterSystems and Developer Community badges and certifications you have on Credly will be visible in your DC profile after your Open Exchange apps and before your Global Masters badges.
In this article we are going to demonstrate the great potential that IRIS/HealthConnect makes available to all its users with the use of Embedded Python and we are going to do it by developing a small production that will allow us to recognize and identify the faces present in a JPG file from some images that we will use as a reference.
Today we continue expanding our last article by sharing information about some features we added to our portal. We will include a pinch of CSS to visualize the available data better and export it. Finally, we will study how to add some filtering and ordering options. By the end of this article, you should be able to display a complete simple query beautifully.
In the sample below, an image file is encoded into a Base64 string in a class property, saved, decoded again with Base64, and restored to another file.
【Usage class】
Class User.test Extends %Persistent
{
Property pics As %GlobalBinaryStream;
}
In my previous articles, I described my Command Line Extension to NativeAPI. Of course, this is also available for any other NativeAPI package. So I created this example as a demo for the actual Java Contest.
The package contains also an IRIS server in Docker for the demo It is evident that it also works with any remote IRIS server. You just have to provide it with my NativeAPI CommandLine Extension.
In 2021, I participated as an InterSystems mentor in a hackathon, where a newcomer to FHIR asked me if there was a tool to transform generic JSON data containing basic patient information into FHIR format. I informed her that I didn't know anything like that, unfortunately.
But that idea stays in my mind...
Several months later, in 2022, I came up with an idea to experiment: to train a named entity recognition (NER) to identify FHIR elements into generic texts. The training involved synthetic FHIR data generated by Synthea and the spaCy Python library.
InstallFoundation method is missing (IRIS 2023.2+)
Recently IRIS 2023.2 was released. This version removed this method InstallFoundation from this class HS.HC.Util.Installer. This was a private method and it was not documented. But it was widely used by the community to install FHIR server.
So if you encounter this error:
<METHOD DOES NOT EXIST> *InstallFoundation,HS.HC.Util.Installer
While build a demo our your own FHIR server, you can fix it by replacing this line:
In our previous article we saw how to capture DICOM type files located in a folder in our server and how we could send them to a PACS software (in our case the ORTHANC open source solution) for storage and consultation. Well, in this article we are going to deal with the opposite movement.
A simple data analysis example created in IntegratedML and Dashboard
Based on InterSystems' Integrated ML technology and Dashboard, automatically generate relevant predictions and BI pages based on uploaded CSV files. The front and back ends are completed in Vue and Iris, allowing users to generate their desired data prediction and analysis pages with simple operations and make decisions based on them.