Deep Papers
Deep Papers is a podcast series featuring deep dives on today’s most important AI papers and research. Hosted by Arize AI founders and engineers, each episode profiles the people and techniques behind cutting-edge breakthroughs in machine learning.
Deep Papers
Demystifying Chronos: Learning the Language of Time Series
This week, we’ve covering Amazon’s time series model: Chronos. Developing accurate machine-learning-based forecasting models has traditionally required substantial dataset-specific tuning and model customization. Chronos however, is built on a language model architecture and trained with billions of tokenized time series observations, enabling it to provide accurate zero-shot forecasts matching or exceeding purpose-built models.
We dive into time series forecasting, some recent research our team has done, and take a community pulse on what people think of Chronos.
To learn more about ML observability, join the Arize AI Slack community or get the latest on our LinkedIn and Twitter.