Google's TabFM voorspelt tabelgegevens zonder apart training per dataset

Google has introduced TabFM, a foundation model that predicts patterns in tabular data without requiring separate training for each dataset. The approach uses in-context learning to handle unseen tables, potentially eliminating the need for extensive hyperparameter tuning and retraining cycles that typically plague tabular data analysis.