AI Vision Language Model

Utilizing the vast MIMIC-IT dataset, consisting of 2.8 million instruction-response pairs derived from images and videos, Otter emerges as a formidable AI tool. With its ability to create conversational contexts and tap into in-context information, Otter effectively enhances the performance of vision-language models (VLMs) in perception, reasoning, and planning. Trained extensively on the MIMIC-IT dataset, Otter's proficiency in multi-modal perception is truly exceptional, seamlessly aligning with the intentions of its users. Notably, the MIMIC-IT dataset is impressively diverse and creative, boasting support for eight languages, making Otter a genuinely multilingual tool. With applications ranging from general scene understanding to optimizing comprehension in augmented reality headsets, this AI vision-language model is poised to revolutionize research in multimodal in-context instruction tuning and vision-language models.