Moirai: Time Series Foundation Models for Universal Forecasting

The future of predictive analytics: Explore Moirai, Salesforce’s new foundation model for advanced time series forecasting

This post was co-authored with Rafael Guedes.

The development of time series foundation models has been accelerating over the last two quarters, and we have been witnessing the release of a new model nearly every month. It started with TimeGPT [1] in the last quarter of 2023, and since then, we saw the release of Lag-Llama [2], Google releasing TimesFM [3], Amazon releasing Chronos [4], and Salesforce releasing Moirai [5].

To understand the growing interest in foundation models, we should define their core capability: zero-shot inference. It refers to the ability to accurately perform tasks or make predictions on data that these models have never encountered during their training phase. This ability has been explored for models applied across various domains, such as natural language processing (NLP), computer vision, and multimodal tasks (combining text, images, etc.). The term “zero-shot” comes from the idea that the model sees “zero” examples from a specific task or data domain during training yet can “shoot” or aim at performing tasks in that area effectively. The term was introduced in the paper “Zero-Shot Learning with Semantic Output Codes,” authored by Hinton et al. and presented at the NIPS…