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.

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 ...

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 ...

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 ...

This new environment will require greater focus on extensive downstream development efforts ... more effective knowledge management and effective data-mining tools are going [to be developed ...