Just-In-Time Learning
Just-in-time learning enables AI models to acquire knowledge as needed, enhancing adaptability and decision-making in real-time scenarios.
Just-in-time learning is an approach where knowledge is acquired at the moment it is needed, rather than in advance. This method is particularly relevant in AI, where models can learn from real-time data inputs, allowing for immediate adaptation to new situations. Just-in-time learning can enhance decision-making processes in dynamic environments, such as robotics and autonomous systems.