What is the purpose of using AI systems with self-supervised learning?

The purpose of using AI systems with self-supervised learning is to enable machines to learn from unlabelled data. This learning approach allows AI models to create their own labels from the data available, effectively allowing the system to extract patterns and features without the need for extensive human intervention in the labeling process. This is particularly advantageous as it significantly reduces the time and cost associated with the data preparation phase, which typically requires labeled datasets for supervised learning. Self-supervised learning thus empowers AI systems to harness vast amounts of unlabelled data, facilitating improved learning outcomes and enabling these systems to generalize better to new, unseen data. This capability is essential in many real-world applications where acquiring labeled data is challenging or impractical.