Hi Developers,

Please welcome the new video, specially recorded by @Zhong.Li for the InterSystems IRIS AI Programming Contest:

IntegratedML-Template Demo

https://www.youtube.com/embed/YxpMc3sODxk
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Article
· Apr 8, 2019 4m read
Should we use computers?

The titular question was quite relevant and often discussed some thirty years ago. The thought went: “Sure, there are industries where computers are the norm, but in my industry we got just fine so far, the benefits are questionable, problems innumerable and unsolved. Can we continue as before or should we embrace this new technology?”

Today, everyone asks the same question but about Machine Learning and Artificial Intelligence. The doubts are the same – lack of expertise, lack of known path, perceived irrelevancy to the industry.

Yet, as before, the correct, even the only possible answer is a resounding yes. Read on to find out why.

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Hi Developers!

Here're the technology bonuses for the InterSystems IRIS AI contest that will give you extra points in the voting.

IntegratedML usage - 4 points

Use InterSystems IntegratedML in you AI/ML solution. Here is the template that uses it.

Be sure that the IRIS version is not less than 2021. The latest ML images with ZPM are:

intersystemsdc/iris-ml-community:2021.1.0.215.0-zpm
intersystemsdc/irishealth-ml-community:2021.1.0.215.0-zpm

R Gateway and Python gateway usage - 4 points

InterSystems IRIS 2021 release contains two new features - R gateway and Python gateway. Here is the template on how to use the R gateway. Here is a short demo of how to use it.

Embedded Python usage - 4 points

Embedded Python is a very new feature of InterSystems IRIS that gives you the option to use python as a "first-class citizen" in backend business logic development with InterSystems classes. Short demo of Embedded Python.

Embedded python could be used in "on-demand" images that could be delivered via InterSystems Early Access Program (EAP) if you refer to python-interest@intersystems.com.

Here is the template package on how to use Embedded Python deployable with ZPM. Don't forget to change the image to the one you get from the Early Access program.

PMML usage - 4 points

PMML - Predictive Modelling Markup Language - can be used to build AI/ML solutions with InterSystems IRIS. Check with documentation.

There is an example in Open Exchange on how to use PMML.

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Hi everyone.
We are a team of company "Constructor" and we develop cutting edge cartographic systems. Recently the amount of image data skyrocketed so we want to give our users the ability to tie images to places automatically. For that, we want to use AI/ML technologies and we have a cool task for you.

https://cloud.mail.ru/public/pHbC/4r7Z58m6f/

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Hi Developers,

The new video from Global Summit 2019 is available on InterSystems Developers YouTube:

Introducing Analytic Workflows

https://www.youtube.com/embed/i32l5ayptaQ
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Hi Community,

Please welcome the new video on InterSystems Developers YouTube:

Best Practices for In-Platform AI

https://www.youtube.com/embed/K2xm6LIVA6U
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Introduction

In InterSystems IRIS 2024.3 and subsequent IRIS versions, the AutoML component is now delivered as a separate Python package that is installed after installation. Unfortunately, some recent versions of Python packages that AutoML relies on have introduced incompatibilities, and can cause failures when training models (TRAIN MODEL statement). If you see an error mentioning "TypeError" and the keyword argument "fit_params" or "sklearn_tags", read on for a quick fix.

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Hi Community,

This week we have two new videos from Global Summit 2019. Please welcome:

1. An ML Toolkit for InterSystems IRIS: Co-Innovation in Healthcare

https://www.youtube.com/embed/o0T0AgvxaNk
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Hi Community!

Welcome the new video from Global Summit 2019 on InterSystems Developers YouTube:

Reducing Readmissions with Machine Learning

https://www.youtube.com/embed/RtiBJy9ScXc
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As an AI language model, ChatGPT is capable of performing a variety of tasks like language translation, writing songs, answering research questions, and even generating computer code. With its impressive abilities, ChatGPT has quickly become a popular tool for various applications, from chatbots to content creation.
But despite its advanced capabilities, ChatGPT is not able to access your personal data. So in this article, I will demonstrate below steps to build custom ChatGPT AI by using LangChain Framework:

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This article shares analysis in solution cycle for the Open Exchange application TOOT ( Open Exchange application )

The hypothesis

A button on a web page can capture the users voice. IRIS integration could manipulate the recordings to extract semantic meaning that IRIS vector search can then offer for new types of AI solution opportunity.

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Fixing the terminology

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.

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Hi Community

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.

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The recording of Anton Umnikov's It's Machine Learning, Not Rocket Science! webinar is now available on learning.intersystems.com.

In it, Anton provides a great, high-level introduction to machine learning and shows why you don't need to be a "unicorn" data scientist to start using machine learning to your advantage!

Watch it now

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Hi Community!

Please welcome a new video on InterSystems Developers YouTube Channel:

InterSystems IRIS from Spark to Finish

https://www.youtube.com/embed/W53PSUkiuS0
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Hi Community,

The new video from Global Summit 2019 is already on InterSystems Developers YouTube:

InterSystems IRIS Roadmap: Analytics and AI

https://www.youtube.com/embed/W2zvl3BO1lA
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Challenges of real-time AI/ML computations

We will start from the examples that we faced as Data Science practice at InterSystems:

  • A “high-load” customer portal is integrated with an online recommendation system. The plan is to reconfigure promo campaigns at the level of the entire retail network (we will assume that instead of a “flat” promo campaign master there will be used a “segment-tactic” matrix). What will happen to the recommender mechanisms? What will happen to data feeds and updates into the recommender mechanisms (the volume of input data having increased 25000 times)? What will happen to recommendation rule generation setup (the need to reduce 1000 times the recommendation rule filtering threshold due to a thousandfold increase of the volume and “assortment” of the rules generated)?
  • An equipment health monitoring system uses “manual” data sample feeds. Now it is connected to a SCADA system that transmits thousands of process parameter readings each second. What will happen to the monitoring system (will it be able to handle equipment health monitoring on a second-by-second basis)? What will happen once the input data receives a new bloc of several hundreds of columns with data sensor readings recently implemented in the SCADA system (will it be necessary, and for how long, to shut down the monitoring system to integrate the new sensor data in the analysis)?
  • A complex of AI/ML mechanisms (recommendation, monitoring, forecasting) depend on each other’s results. How many man-hours will it take every month to adapt those AI/ML mechanisms’ functioning to changes in the input data? What is the overall “delay” in supporting business decision making by the AI/ML mechanisms (the refresh frequency of supporting information against the feed frequency of new input data)?

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Introducing Smart Clinical Sidechick — the intelligent, no-drama partner your EHR wishes it could be. She reads FHIR data in real time, interprets lab results without ghosting, and explains clinical alerts like she actually cares. Built with GPT-4 brains and YAML sass, she’s not here to replace your main EHR—just to make it look bad. Tired of irrelevant alerts and cryptic warnings? Sidechick serves up real, explainable insights, not vague “elevated risk” vibes. And when your backend crashes, she doesn’t panic—she self-heals.

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Hi Community!

New video "Deploying Shards Using InterSystems Cloud Manager" is available now on InterSystems Developers YouTube:

https://www.youtube.com/embed/UV1zYRQUPlw
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Hi,

While we're working on a new data product supporting the analytics development process, we'd like to test some of the UX (User eXperience) design elements on a real audience. If you've got some battle scars from earlier analytics work and are interested in participating, please complete this survey and we'll get in touch when we have something to show!

Feel free to share this survey with your data-savvy friends and colleagues if you think they match the profile.

Thanks in advance for your participation!

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Hi Community,

Please welcome the new video on InterSystems Developers YouTube Channel:

Operationalizing "Machine Learning" Experiences From the Field

https://www.youtube.com/embed/8yN-rh5g21s
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Keywords: IRIS, IntegratedML, Machine Learning, Covid-19, Kaggle

Continued from the previous Part I ... In part I, we walked through traditional ML approaches on this Covid-19 dataset on Kaggle.

In this Part II, let's run the same data & task, in its simplest possible form, through IRIS integratedML which is a nice & sleek SQL interface for backend AutoML options. It uses the same environment.

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