#Generative AI (GenAI)

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Generative AI refers to algorithms and models in artificial intelligence that are capable of generating new data or content that is similar to existing data. These models are trained on large datasets and learn to generate new examples that mimic the patterns and characteristics of the original data.

Discussion Evgeny Shvarov · Feb 14

Hi developers!

I'm testing vibecoding with ObjectScript and my silicon friend created a code-block that got me thinking "what's wrong"?

Here is the piece of code:

for01

AI wanted to quit from a method with a return value. Good intention, but bad use of the command.

And ObjectScript compiler compiles this code with no error(?) (syntax linter in VSCode says it's a syntax, kudos @Brett Saviano ).

But in action, it produces <COMMAND>, of course.

Wanted to share with you as this is a good case where return

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Discussion Benjamin De Boe · Dec 4, 2025

Hi,

We're working on new capabilities to help you build Agents and AI applications faster with InterSystems IRIS. In order to better understand which entry points and development methodologies would help you most, we've created this brief survey: Building AI solutions with InterSystems IRIS. 

Filling it in should not take much more than 5 minutes, and your feedback on this exciting topic will help us fine tune our designs and prioritize the right features.

Thanks in advance!
benjamin
 

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Discussion Benjamin De Boe · Oct 29, 2025

Hi, 

We very much appreciate the interest in the Developer Community for IRIS Vector Search and hope our technology has helped many of you build innovative applications or advanced your R&D efforts. With a dedicated index, integrated embeddings generation, and deep integration with our SQL engine now available in InterSystems IRIS, we're looking at the next frontier, and would love to hear your feedback on the technology to prioritize our investments.

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Discussion Yuri Marx · Oct 12, 2025

This anthropic article made me think of several InterSystems presentations and articles on the topic of data quality for AI applications. InterSystems is right that data quality is crucial for AI, but I imagined there would be room for small errors, but this study suggests otherwise. That small errors can lead to big hallucinations. What do you think of this? And how can InterSystems technology help?

https://www.anthropic.com/research/small-samples-poison

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