Joint learning trains multiple AI tasks or models simultaneously, sharing knowledge across them. Rather than training each task independently in isolation, the models learn together and reinforce each other's understanding.
In a virtual assistant, training intent detection and entity recognition together can improve both — because they are interdependent tasks and the shared learning makes each more accurate. This is more efficient than training separately and often produces better overall performance on complex systems where tasks interact.
