Vision-Language Model/VLM
Multi mode model type that can understand and associate both images.
Visual-language models (VLM) are very modlu (multimodal) artificial intelligence models that can work image and text simultaneously and create meaningal bond between them. Classic language models only combine VLMs in a common representation space with a visual encoder (usually a Vision Transformer) while processing text, so that objects in the visual can associate the scene, font or emotional tone with text. During the training, the model often learns on millions of visual-text pairs (e.g. a photo and its description) collected from the internet, which words of the visual match, so it can describe it when it sees a new visual, read the text inside, or respond to visual-based questions.
VLMs are one of the fastest growing areas of artificial intelligence today because the real world is mostly not a single fashion: a bill carries both visual and textual information, a product photo contains both shapes and articles. Up-to-date large models like GPT-4o, Google Gemini and Claude have become available in tasks such as graphic interpretation, handwriting reading, diagram analysis and visual reasoning. This ability prepares grounds for practical applications such as robotics, medical imaging, accessibility tools and autonomous driving.
VLMs are one of the fastest growing areas of artificial intelligence today because the real world is mostly not a single fashion: a bill carries both visual and textual information, a product photo contains both shapes and articles. Up-to-date large models like GPT-4o, Google Gemini and Claude have become available in tasks such as graphic interpretation, handwriting reading, diagram analysis and visual reasoning. This ability prepares grounds for practical applications such as robotics, medical imaging, accessibility tools and autonomous driving.