This post is from the WWDC26 Foundation Models Q&A.
The Foundation Models framework is clearly designed around language, but there's a large class of on-device AI tasks that are not language tasks at all. Time series forecasting is one example think energy consumption modeling, or sensor anomaly detection. These models take sequences of numeric data and output probabilistic forecasts. No text involved at any layer.
- Is there any intention to extend Foundation Models or a sibling framework to non-language modalities specifically structured numeric and time series inference
