If You Learn Slowly Enough, You Won’t Need to Learn Anything—Applying the TabFM Prediction Framework to Quantitative Trading

1Key Takeaways

• Recently, Google Research released TabFM, a foundation model designed for tabular classification and regression tasks.
• It attempts to compress model training, hyperparameter search, and complex feature engineering in traditional tabular machine learning into a more direct workflow: give the model a set of labeled historical samples, provide one new row, and let the model make a prediction in context.
• (Google Research) When I first saw this framework, the first application that came to mind was….