The term "joint training for multimodal AI" belongs primarily to the categories of artificial intelligence, automation and digital transformation. This involves artificial intelligence not only processing one type of data such as text, images or sounds, but also learning and linking different types of information simultaneously.
Imagine you want to develop an AI that helps doctors make diagnoses. During joint training for multimodal AI, the system simultaneously learns from X-ray images (pictures), patient reports (texts) and heartbeat recordings (sounds). This enables it to recognise correlations that a person alone might overlook.
This joint training makes AIs more flexible and efficient because they can learn from different sources and make better decisions. For example, chatbots are created that not only describe a product, but also understand images and explanatory videos and combine them appropriately.
The aim is to develop more versatile and intelligent tools that offer real added value for companies. Joint training for multimodal AI is therefore an important trend in the development of modern, smart solutions.















