Once you train a machine learning model on training examples—whether it’s on images, audio, raw text, or tabular data—what you get is a set of numerical parameters.

Filling gaps in data sets or identifying outliers—that's the domain of the machine learning algorithm TabPFN, developed by a team led by Prof. Dr. Frank Hutter from the University of Freiburg ...

Databricks has acquired Tabular, a data management startup, in its quest to build a common standard for data lakehouses.