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At the end of the day, if training or doing inference on the ML model is massively more costly in time or compute, you'll iterate much less with it.

I also think it's a dead end to try to have foundation models for "time series" - it's a class of data! Like when people tried to have foundation models for any general graph type.

You could make foundation models for data within that type - eg. meteorological time series, or social network graphs. But for the abstract class type it seems like a dead end.




These models may be helpful if they speed up convergence when fine tuned on business-specific time series.


so this TimesFM is also in the same category as TimeGPT from nixtlaverse?




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