#Artificial Intelligence (AI)

Hey Developers,

We'd like to invite you to join our next contest dedicated to creating AI/ML solutions that use Cloud SQL to work with data: 

🏆 InterSystems IRIS Cloud SQL and IntegratedML Contest 🏆

Duration: April 3 - April 23, 2023

Prize pool: $13,500

​Keywords: ChatGPT, COS, Lookup Table, IRIS, AI 

Purpose

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. 

Lookup tables

One of the simplest tasks could be Lookup tables.

Fun or No Fun - how serious is it?

Large language models are stirring up some phenomena in recent months. So inevitably I was playing ChatGPT too over last weekend, to probe whether it would be a complimentary to some BERT based "traditional" AI chatbots I was knocking up, or rather would it simply sweep them away. 
A thought comes to mind while playing. By going slightly theoretical or philosophical, eventually interoperability standards such as HL7 and FHIR etc are kind of "languages", right? HL7 has its own grammar, rules, vocabulary and even dialects - every system speaks its own tone.

Morning all,

I got access to the new Bing this morning and thought I would try out some things on it. Below are a series of screenshots of what I searched and the results.
Please share your experiences here too.

 Searching for help with arrays:

 A search for a Python related topic:

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!

Hello everyone, this is with great pleasure that I announce the V2 of my application 'Contest-FHIR'.

In this new version, I used new tools and techniques I discovered at the EUROPEAN HEALTHCARE HACKATHON in which I was invited by InterSystems as a guest and as a mentor to display the multiple projects I did in my intership back in April 2022.

Today I present to you the V2 of my application, it can now transform CSV to FHIR to SQL to JUPYTER notebook.

This is for me a really huge step in InterSystems technologies and I think this tool will be used for many other purpuse and cases.

Easy, easy, I'm not promoting a war against the machines in the best sci-fi way to avoid world domination of Ultron or Skynet. Not yet, not yet 🤔

I invite you to challenge the machines through the creation of a very simple game using ObjectScript with embedded Python.

I have to say that I got super excited with the feature of Embedded Python on InterSystems IRIS, it's incredible the bunch of possibilities that opens to create fantastic apps.

Let's build a tic tac toe, the rules are quite simple and I believe that everyone knows how to play.

Hi all. Today we are going to install Jupyter Notebook and connect it to Apache Spark and InterSystems IRIS.

Note: I have done the following on Ubuntu 18.04,  Python 3.6.5.

Introduction

If you are looking for well-known, widely-spread and mainly popular among Python users notebook instead of Apache Zeppelin, you should choose Jupyter notebook. Jupyter notebook is a very powerful and great data science tool. it has a big community and a lot of additional software and integrations.

Hi, guys, I need some help, I'm getting an XML from the Matrix application and in the header there's an Action that has the property mustUndertand = 1

<s:Envelope xmlns:s="http://schemas.xmlsoap.org/soap/envelope/">
  <s:Header>
    <Action s:mustUnderstand="1" xmlns="http://schemas.microsoft.com/ws/2005/05/addressing/none">http://protocolomatrix.matrixsaude.com/RecebeResultado</Action&gt;
  </s:Header>
  <s:Body xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema">

No BS Receives but cannot handle the action.

In this article, I am trying to identify the multiple areas to develop the features we can able to do using python and machine learning.

Each hospital is every moment trying to improve its quality of service and efficiency using technology and services. 

The healthcare sector is one of the very big and vast areas of service options available and python is one of the best technology for doing machine learning.

In every hospital, humans will come with some feelings, if this feeling will understand using technology is make a chance to provide better service.

What will the ideal learning path for a DataScience & AI aspirant ? 

Hey Community, 

Don't miss the latest videos on InterSystems Developers YouTube channel:

⏯ IntegratedML Update from the Field

Maternal Risk can be measured 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 scientist Yasir Hussein Shakir published a very useful dataset for training ML algorithms in the detection/prediction of Maternal Risk. This publication can be found on the largest and best known data repository for ML, Kaggle at https://www.kaggle.com/code/yasserhessein/classification-maternal-healt….

Kidney Disease 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 scientist Akshay Singh published a very useful dataset for training ML algorithms in the detection/prediction of kidney disease. This publication can be found on the largest and best known data repository for ML, Kaggle at https://www.kaggle.com/datasets/akshayksingh/kidney-disease-dataset.

About the Dataset

The kidney disease dataset has the following metadata information (source: https://www.kaggle.

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.

The diabetes dataset has the following metadata information (source: https://www.kaggle.

Hi all, 

any news about support of the IRIS platform in the DBeaver?  I only found this  https://github.com/dbeaver/dbeaver/issues/6289  Github issue. They are waiting for a new version of the JDBC driver. 

Thanks for the answer

All of us know that money is important. We constantly need to monitor all expenses to avoid looking back to the bank statement and thinking: “So, where’s my money?”

To evade financial stress, we must keep an eye on the inflow and outflow of money into our accounts.It is also important to tack when and how we spend and earn. Manually recording all transactions in order to understand where our money goes requires an effort. It demands consistency, and it is boring. Today there is a bunch of mobile or SaaS options that help you manage your finances.

Hi Community,

Don't miss the new video on InterSystems Developers YouTube:

⏯ Exploring Machine Learning with R Language Gateway

Hey Community,

Enjoy watching the new video on InterSystems Developers YouTube channel:

⏯ Creating Virtual Models with InterSystems IRIS Adaptive Analytics

* In-Platform Agent-Based Simulation of a Connected Factory Cluster

Author: Sergey Lukyanchikov, InterSystems

1. Purpose

In this paper we prototype and explore how multiple agent-based models of robotic factories connected to other robotic factories (represented by their respective models) can be orchestrated using an all-purpose data platform – thereby simulating descriptive and predictive properties of a group of factories (a factory cluster).

Hi Community,

Please welcome the new video from #VSummit20:

⏯ Showcasing Health Insight & IntegratedML for Healthcare Applications

Hi Community,

We're pleased to invite you to the upcoming webinar in Spanish called "IntegratedML - Creating ML models in minutes"!

Date & Time: September 30, 4:00 PM (CEST)

Speaker: @Eduardo Anglada, Sales Engineer, InterSystems Iberia

Hi Community,

We're pleased to invite you to the online meetup with the winners of the InterSystems AI contest!

Date & Time: Friday, July 30, 2021 – 11:00 AM EDT

What awaits you at this Virtual Meetup? 

• Our winners' bios.
• Short demos on their applications.
• An open discussion about technologies being used. Q&A. Plans for the next contests.

Uber type application and database management system wanted.

Reaching out to the development community.  Here at POLC we are planning to soon launch a new ride hailing app called POLC.  Wanted to know if any developers on this forum has built a similar system before?   Please DM me on +27 66 243 1618

Hey Developers,

The InterSystems AI programming contest is over. And now it's time to announce the winners! 

Are you excited?

A storm of applause goes to these developers and their applications:

Hi Developers!

We had a set of technology bonuses for the InterSystems AI/ML contest.

And here is how projects collected it:

Hey Developers,

This week is a voting week for the InterSystems AI programming contest! So, it's time to give your vote to the best solutions built with InterSystems IRIS.

🔥 You decide: VOTING IS HERE 🔥

How to vote? Details below.

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)?

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.