Multimodal language models are revolutionizing the way we interact with technology. They are trained on a vast array of data, ranging from traditional textual datasets to non-textual data like images, audio, and video, allowing them to understand and interpret a wide range of inputs. This means that they can generate responses in a multitude of modes, making them even more versatile than large language models. From understanding the meaning behind an image to generating responses to a spoken question, multimodal language models have the potential to fundamentally change the way we communicate with machines.
