prompt engineering steps, upstream predictive AI models, downstream LLMs, and integration with downstream systems,” says Kjell Carlsson, head of data science strategy and evangelism at Domino.

Time efficiency of analysis is especially critical when investigating quality excursions. During this time, the line may be ...

That’s because data engineering involves dealing with strict schemas, tightly coupled pipelines and reproducibility requirements, and even the smallest of errors can totally corrupt downstream ...

This is one of the core objectives of the group, to give more information to those downstream and encourage collaboration through reliability of the BIM data. One quote states ... with leaders in the ...

There're both engineering & regulatory hurdles to hop through." AI models have to be trained on billions of data points and there's no way around this. Some datasets have very clear rules for ...