data collection and labeling, storage and computing (e.g., data cleaning and preprocessing). Best For: Enterprises needing diverse, real-world, and structured datasets to train or fine-tune AI models.

However, the current climate has given rise to a turning point for data collection, with the possibility of it being used to do more good. Below, I will explore all the facets of data in today’s ...

It can occur at various stages of the AI lifecycle, including data collection, preprocessing, algorithm design, and decision-making. Bias can be unintentional, arising from historical imbalances ...