Microsoft Introduces Multimodal Kosmos-2.5
Microsoft is breaking new ground in the realm of multimodal AI with the introduction of Kosmos-2.5, a literate model designed for the intricate task of machine reading of text-intensive images. Building on the success of its predecessor, Kosmos-1, and Kosmos-2, Microsoft’s Kosmos-2.5 boasts an impressive array of features and capabilities that are set to transform the landscape of image-text understanding. Click here to read the paper. Kosmos-2.5 has been meticulously pre-trained on vast datasets containing text-intensive images. This extensive training equips Kosmos-2.5 with exceptional proficiency in two closely intertwined transcription tasks: Spatially-Aware Text Blocks: Kosmos-2.5 can expertly generate text blocks within images while accurately assigning each block its precise spatial coordinates. This breakthrough capability enhances the model’s understanding of text in images, enabling it to provide structured and coherent textual descriptions of image content. Structured Markdown Text Output: In addition to spatial awareness, Kosmos-2.5 excels in producing structured text output in markdown format. This ensures that not only is the text extracted from images, but is also presented in a structured and stylized manner. https://twitter.com/ITica007/status/1704786116375675238 The remarkable capabilities of Kosmos-2.5 are achieved through a shared Transformer architecture, task-specific prompts, and adaptable text representations. This multimodal literate model is a versatile tool that can be harnessed for a wide range of real-world applications involving text-rich images. The model has undergone extensive testing, demonstrating its proficiency in end-to-end document-level text recognition and image-to-markdown text generation. Furthermore, Kosmos-2.5 can be effortlessly adapted to various text-intensive image understanding tasks using different prompts through supervised fine-tuning. The introduction of Kosmos-2.5 signifies a significant step towards the future scaling of multimodal large language models. This groundbreaking work by Microsoft is poised to have a transformative impact on the field of AI and image-text understanding. Kosmos-1 showed that Language is not all that you need. It showcased the potential of integrating language, action, multimodal perception, and world modeling for the advancement of artificial general intelligence (AGI). Kosmos-2.5 is the next step.
The model has been meticulously pre-trained on vast datasets containing text-intensive images.
Building on the success of Kosmos-1, and Kosmo-2, Microsoft's Kosmos-2.5 boasts an impressive array of features and capabilities.
["AI Research"]
["Go", "TPU", "programming_languages:R", "AI", "Modal", "programming_languages:Go", "AI Research", "Ray", "multimodal AI", "transformer architecture", "R"]
["AI", "multimodal AI", "Ray", "TPU", "R", "Go", "transformer architecture", "Modal", "programming_languages:R", "programming_languages:Go"]
Mohit writes about AI in simple, explainable, and often funny words. He's especially passionate about chatting with those building AI for Bharat, with the occasional detour into AGI.