What is Distributed Artificial Intelligence (DAI)?

Attempts to find a “bullet-proof” definition have not produced result: it seems like the term is slightly “ahead of time”. Still, we can analyze semantically the term itself – deriving that distributed artificial intelligence is the same AI (see our effort to suggest an “applied” definition) though partitioned across several computers that are not clustered together (neither data-wise, nor via applications, not by providing access to particular computers in principle). I.e., ideally, distributed artificial intelligence should be arranged in such a way that none of the computers participating in that “distribution” have direct access to data nor applications of another computer: the only alternative becomes transmission of data samples and executable scripts via “transparent” messaging. Any deviations from that ideal should lead to an advent of “partially distributed artificial intelligence” – an example being distributed data with a central application server. Or its inverse. One way or the other, we obtain as a result a set of “federated” models (i.e., either models trained each on their own data sources, or each trained by their own algorithms, or “both at once”).

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In Studio you could open a class directly via it's name, without having to traverse the package tree with multiple clicks until arriving at the desired class.

You would Ctrl + O or (File -> Open) and be able to simply type in the class name, for example:

You press Enter, and viola - the class is opened.

How do you achieve this in VSCode?

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If you create your own Language Extensions to Object you mostly have to find the
proper %ZLANGC00 or %ZLANGV00 or %ZLANGF00 and add the extensions manually.
A few utilities do it already automatically (ZPM, ZME, ..)
This utility allows you to add your extensions programmatically. (eg. at first run, or during installation)
I found this quite useful for my Docker-based demos as it all happens at the start time.

It is related to these articles

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Article
Robert Cemper · Mar 27, 2021 3m read
IRIS easy ECP workbench

Testing ECP-based applications often take quite some effort for setup and preparation.
I have created a Docker-based workbench that allows you to have it quick at hands.
And if you crash it? You just give your containers a fresh start.
The whole setup runs code-based during the start-up of your instance.
In that sense, it is also a portable coding example using ZPM and the objectscript-docker-template

 see Video

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cAdvisor (short for container Advisor) analyzes and exposes resource usage and performance data from running containers. cAdvisor exposes Prometheus metrics out of the box. 

https://prometheus.io/docs/guides/cadvisor/

Prometheus is integrated in SAM. This makes it possible to leverage the cAdvisor metrics and expose them via Prometheus and Grafana.

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Article
Timothy Leavitt · Mar 17, 2021 3m read
Making the most of $Query

I ran into an interesting ObjectScript use case today with a general solution that I wanted to share.

Use case:

I have a JSON array (specifically, in my case, an array of issues from Jira) that I want to aggregate over a few fields - say, category, priority, and issue type. I then want to flatten the aggregates into a simple list with the total for each of the groups. Of course, for the aggregation, it makes sense to use a local array in the form:

agg(category, priority, type) = total

Such that for each record in the input array I can just:

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Purpose

Most CloudFormation articles are Linux-based (no wonder), but there seems to be a demand for automation for Windows as well. Based on this original article by Anton, I implemented an example of deploying a mirror cluster to Windows servers using CloudFormation.I also added a simple walk through.
The complete source code can be found here.

Update: 2021 March 1 I added a way to connect to Windows shell by public key authentication via a bastion host as a one-liner.

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Hi Community,

Did you know about OWASP and Top Ten Web Application security risks to your Web API or Web Apps?

OWASP is a community foundation created to help us to improve the security of web apps/web APIs. OWASP do the web apps more secure through its community-led open source software projects, hundreds of chapters worldwide, tens of thousands of members, and by hosting local and global conferences.

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Article
Robert Cemper · Mar 5, 2021 3m read
Using ECP across IRIS and Caché

Migration from Caché to IRIS can be quite a challenge if your code is grown over many years
and probably not so clean structured as you may like it. So you face the need to check your
migrated code against some reference data. A few samples might not be a problem,
but some hundred GB of data for testing might be.  

A possible step could be to have your fresh code in IRIS but leave your huge datastore on Caché and connect both environments over ECP.  I have created a demo project that gives you the opportunity to try this based on 2 Docker images with IRIS and with Caché connected over ECP.

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Organizations around the world lose an estimated five percent of their annual revenues to fraud, according to a survey of Certified Fraud Examiners (CFEs) who investigated cases between January 2010 and December 2011. Applied to the estimated 2011 Gross World Product, this figure translates to a potential total fraud loss of more than $3.5 trillion (source: https://www.acfe.com/press-release.aspx?id=4294973129).

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Article
Hao Wang · Mar 4, 2021 1m read
What is accuracy, accuracy, recall

Accuracy rate is a measure of our prediction results, and it is a measure of how many of the predicted positive samples are actually positive.
The recall rate is for our original sample, and it shows how many positive examples in the sample were correctly predicted.
Accuracy = Predicted correctly/All
If we want to be able to retrieve as much content as possible, this is the pursuit of "recall ratio", namely A/(A+C), the bigger the better.

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Hello, developers!

In this article, I will show you how to configure FHIR repository + OAuth2 authorization server/resource server on IRIS for Health following the previous article.

In Part 1, we introduced the preliminary preparations, configuring the OAuth2 authorization server, and obtaining the access token.
Part 2 will show you how to build an FHIR repository and configure an OAuth2 client/resource server.

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Recently I wanted to get a list of all cached queries and their texts. Here's how to do that.

First create an SQL Procedure returning Cache Query text from a Cached Query routine name:

Class test.CQ
{

/// SELECT test.CQ_GetText()
ClassMethod GetText(routine As %String) As %String [ CodeMode = expression, SqlProc ]
{
##class(%SQLCatalog).GetCachedQueryInfo(routine)
}

}

And after that you can execute this query:

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