Google debuts TimesFM-3 for multivariate time series forecasting
Google has released TimesFM-3, its latest time series AI model designed to forecast multiple related variables at once. Unlike earlier versions limited to single-variable predictions, TimesFM-3 handles complex scenarios—like using both sales and weather data to project demand. It has 330 million parameters and was trained on over 1 trillion time points. Google says it beats previous models on major forecasting benchmarks, all without extra tuning.
- Handles multiple time series at once
- 330 million parameters, trained on over 1 trillion data points
- Works without task-specific fine-tuning
- Uses future known events for better accuracy
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