4 docs tagged with "storage"

User tracking, user data collection and targeting in things like advertisements are responsible for significant energy use in many digital products, and services.

It's better to maximise storage utilisation so the storage layer is optimised for the task, not only in terms of energy proportionality but also in terms of embodied carbon. Two storage units running at low utilization rates will consume more energy than one running at a high utilization rate. In addition, the unused capacity on the underutilised storage unit could be more efficiently used for another task or process.

From an embodied carbon perspective, it's better to identify and remove unused storage resources and implement automated retention policies so we are efficient with hardware and ensure the storage layer is optimized for the task.

Efficient storage formats for both training data and model artifacts are essential to reduce storage costs, network bandwidth, and computational overhead in AI/ML development pipelines.