Improving AI using transfer and few-shot learning techniques

Specifically, transfer learning has shown great success in computer vision. By utilizing pre-trained models, specifically those trained on the ImageNet dataset, it becomes feasible to modify them for specific tasks, consequently diminishing the need for abundant labeled data and training duration. As a result, this has facilitated the rapid development and integration of AI systems in a range of sectors, including healthcare, manufacturing, and autonomous vehicles.