Slide 9
Slide 9 text
Data Loop Model Loop Challenge/Value
Slow Slow Low freshness, low quality.
Out-of-date models, predictions & trainings with stale data, model
drift results in low model accuracy.
Slow Fast Low freshness, low quality.
Model training is bottlenecked by availability of fresh data. Prediction
latency high or predicted with stale data.
Fast Slow High freshness, low quality.
Fresh data available for predictions, trainings, and observability. Slow
model iteration results in out-of-date model, lower accuracy.
Fast Fast High freshness, high quality.
You want your ML ecosystem to be here.
Combine your data and model loops: why you need both to be fast