Data-Centric AI Requires Rethinking Data Notion

Understand

The transition towards data-centric AI requires revisiting data notions from mathematical and implementational standpoints to obtain unified data-centric machine learning packages.

• Towards this end, this work proposes unifying principles offered by categorical and cochain notions of data, and discusses the importance of these principles in data-centric AI transition.
• In the categorical notion, data is viewed as a mathematical structure that we act upon via morphisms to preserve this structure.
• As for cochain notion, data can be viewed as a function defined in a discrete domain of interest and acted upon via operators.