Tue, 05 May 2026 05:23:38 +0000

A) Unlabeled Data for Training: The Hidden Potential in Raw Data In the fast-evolving world of artificial intelligence (AI) and machine learning (ML), labeled data remains a critical component for training accurate models. However, while labeled data receives significant attention, unlabeled data is emerging as a powerful, often underutilized resource in powering next-generation intelligent systems. ### Why Unlabeled Data Matters Unlabeled data refers to raw, unannotated information collected from various sources—such as text, images, audio, or video—without explicit metadata or labels. Despite lacking direct supervision, this data holds immense potential when applied to modern training strategies. In fact, leveraging unlabeled data is at the heart of several cutting-edge approaches, including self-supervised learning, semi-supervised learning, and large-scale pre-training.