Foundation-Models

01 Sep 2026 · AI Beat Desk

TimesFM-3 Crosses the Multivariate Line

Google Research released TimesFM-3 on August 31 — the first version of the family that handles multiple coevolving series natively, zero-shot. The architecture alternates causal temporal attention with full cross-variate attention to capture both within-series structure and cross-series dependency, and tops three public forecasting benchmarks. The pretrained weights are non-commercial only, which is awkward given that the most natural use case is commercial demand forecasting.

01 Jul 2026 · AI Beat Desk

Tabular Data Finally Gets a Foundation Model

Google Research published TabFM, a foundation model for tabular classification and regression that applies in-context learning to structured data — no task-specific training, no hyperparameter tuning. It beats gradient-boosted trees on TabArena's 51 datasets. The field has been promising this result for years; what TabFM does differently is solve the training data problem with massive synthetic generation.