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There were some developments using LLMs in the timeseries domain which caught my attention.
I toyed with the Chronos forecasting toolkit [1], and the results were predictably off by wild margins [2]
What really caught my eye though was the "feel" of the predicted timeseries -- this is the first time I've seen synthetic timeseries that look like the real thing. Stock charts have a certain quality to them, once you've been looking at them long enough, you can tell more often than not whether some unlabeled data is a stock price timeseries or not. It seems the chronos LLM was able to pick up on that "nature" of the price movement, and replicate it in its forecasts. Impressive!
1: https://github.com/amazon-science/chronos-forecasting
2: https://imgur.com/a/hTRQ38d
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TimesFM (Time Series Foundation Model) for time-series forecasting
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Chronos: Learning the Language of Time Series
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Benchmarking foundation models for time series
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TimeGPT: Production Ready Time Series Foundation Model for Forecasting
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