AI systems can now be designed to learn continuously from new data inputs. This dynamic learning ability allows AI to adapt to changes in user behavior, preferences, and external conditions. For instance, recommendation systems adjust their suggestions based on real-time user interactions, ensuring that they remain relevant and useful.

3. Transfer Learning: This technique allows AI models to apply knowledge gained in one area to different but related areas. For example, an AI trained for image recognition can be adapted for medical imaging with minimal additional training. This adaptability speeds up the deployment of AI in various fields.