Kosmos-2 by Microsoft - Grounding Multimodal Large Language Models to the World

Microsoft Research has introduced Kosmos-2, a Multimodal Large Language Model (MLLM) that can perceive object descriptions and ground text to the visual world. The model represents refer expressions as links and constructs a large-scale dataset of grounded image-text pairs to train the model. Kosmos-2 has the capability to perform tasks such as referring expression comprehension, referring expression generation, and perception-language tasks. This work is an important step towards the development of Embodiment AI and artificial general intelligence.

Benefits

1. Improved multimodal grounding: Kosmos-2 enhances the understanding of refer expressions and phrase grounding by perceiving object descriptions and linking them to visual representations.
2. Enhanced referring expression generation: The model facilitates better multimodal referring by generating accurate and contextually appropriate referring expressions.
3. Perception-language tasks: Kosmos-2 excels in tasks that require the integration of language comprehension and perception, enabling seamless interactions between the two modalities.
4. Language understanding and generation: The AI startup's services empower language understanding and generation tasks, enabling natural and meaningful communication between users and AI systems.
5. Foundation for Embodiment AI: The development of Kosmos-2 establishes the groundwork for the advancement of Embodiment AI, which combines language, multimodal perception, action, and world modeling, bringing us closer to artificial general intelligence.

Use Cases

1. Referring expression comprehension: Kosmos-2 can accurately comprehend referring expressions, allowing for precise identification of objects and locations.
2. Phrase grounding: The AI startup's services excel in grounding phrases to the visual world, enhancing the understanding and contextualization of textual information.
3. Multimodal referring expression generation: The model generates referring expressions that are appropriate and contextually relevant when referring to objects or entities in a visual context.
4. Perception-language tasks: Kosmos-2 enables seamless interactions between language and perception, empowering tasks that require understanding and generating information in a multimodal setting.
5. Language understanding and generation: The AI startup's services enhance language understanding and generation capabilities, facilitating natural and meaningful communication between users and AI systems.