Self-supervised learning techniques in AI
23 November 2024
The advancement of Artificial Intelligence Systems (AIS) hinges significantly on how effectively they can learn from available data. Among the myriad of AI learning paradigms, Self-supervised Learning (SSL) stands out as a transformative approach, offering impressive capabilities for AIS development. Self-supervised learning breaks away from traditional machine learning paradigms by enabling models to learn from unlabeled data, bridging a crucial gap in scenarios where labeled datasets are scarce or expensive to procure. The integration of self-supervised learning techniques into AIS is gaining traction, primarily because these methods ensure that AI systems can continuously learn and adapt without constant human intervention. […]
