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#AI

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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.

Learn more.

Discussion
Eduard Lebedyuk · Sep 16
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Several models, such as DALL-E, Midjourney, and StableDiffusion, became available recently. All these models generate digital images from natural language descriptions. The most interesting one, in my opinion, is StableDiffusion which is open source - released barely a few weeks ago. There's now an entire community trying to leverage it for various use cases.
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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.

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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.

Open Exchange app
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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.

Open Exchange app
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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.

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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

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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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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 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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