TabFM predicts on any table without training
Google Research launches TabFM, a foundation model that predicts on unseen tabular datasets in a single forward pass. By treating tables as in‑context learning prompts, it removes the need for model training, hyperparameter sweeps, and hand‑crafted feature engineering, speeding up churn, fraud, and other enterprise predictions.