Vision language models (VLMs) are a promising subset of multimodal AI, capable of processing the two different modalities of text and image in order to perform a wide range of vision-language tasks — like image captioning, image search and retrieval, text-to-image generation, visual question answering (VQA), and video understanding.
In our previous post on vision language models, we covered some of the basics of their underlying architecture, some of the strategies for training them, and how they can be used. Now, we’ll look at the most…
