
Google Just Released TabFM and It Breaks Everything We Know About ML
AI with Surya · 7:16
Google's TabFM is a foundation model for tabular data that uses a novel two-way attention mechanism (column attention → row compression → ICL transformer) to perform zero-shot classification/regression on arbitrary tables — beating tuned XGBoost without any training on your data, in milliseconds. The key insight: it treats your spreadsheet like an LLM prompt, using labeled rows as context and unlabeled rows as questions, with frozen weights and full attention-weight explainability.
Alösha's take: Neat paradigm shift — the 'floor came up, ceiling didn't move' framing is spot-on; worth understanding the architecture even if the hype is premature.










