NVIDIA's Kumo Relational predicts churn and demand straight from database tables
Sorted AI24 OctNVIDIA released Kumo Relational, a pre-trained model that makes predictions such as churn, demand or fraud directly on a relational database. You write what you want to predict in a short query language, and it pulls past examples from your tables as context, with no task-specific training and no flattening tables into one spreadsheet. NVIDIA says that across 41 tasks on 15 databases it beat supervised models and expert-built gradient-boosted tree pipelines, and that on the SAP SALT enterprise benchmark it beat AutoGluon ensembles by 8% on its ranking metric. These are NVIDIA's own results; it also says supervised models may still win when you have very large training sets. The code is open source (Apache 2.0), the weights are on Hugging Face, and it runs on an NVIDIA GPU or as an NVIDIA NIM.
Why it matters: If you have a churn or demand question sitting in your customer and order tables but no ML team, this could give a first baseline in days rather than weeks. Test it against what you use now on your own past data before trusting it.
Hugging Face (NVIDIA) ↗AI-assisted, reviewed by Sorted AI
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