The successful application of machine learning to understand the behavior of complex real-world systems from healthcare to climate requires robust methods for processing time series data. This type of data is made up of streams of values that change over time, and can represent topics as varied as a patient’s ECG signal in the ICU or a storm system moving across the Earth.Highly capable multimodal foundation models, such as Gemini Pro, have recently burst onto the scene and are able to reason no...