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How foundation models label vehicle fuel telematics, enable custom temporal filters per make/model/year, and address challenges integrating LLMs with time‑series models.
We are using time-series foundation models to label things like fuel data from vehicle telematics, so that we can create custom-tuned temporal filters for all the various vehicle make, model and year across our customers’ fleet. This is a summary of work to date, and where we are heading with this.
MOMENT: open time-series foundation models, masked reconstruction for diverse analytical tasks.
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