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Magma Screenshot
Magma

Magma

Foundation Model for Multimodal AI Agents

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112 Upvotes

About

Magma is presented as the first foundation model for multimodal AI agents, developed by Microsoft Research and collaborators. It aims to bridge verbal, spatial, and temporal intelligence to enable AI agents to perceive the multimodal world and take goal-driven actions across digital and physical environments. The model is pretrained on extensive heterogeneous vision-language datasets, including images, videos, and robotics data, utilizing novel Set-of-Mark (SoM) for action grounding and Trace-of-Mark (ToM) for action planning. Magma demonstrates state-of-the-art performance in UI navigation and robotic manipulation, and competitive results in vision-language tasks, spatial reasoning, and video QA.


Color Palette

Background White

#FFFFFF

70%

Text Black

#000000

20%

Magma Brand Blue/Purple

#5C3E9E

5%

Link Blue

#007bff

5%

Typography

Sans-serif

Headings and Body Text

Aa

Design Review

The design of the Magma landing page is highly functional and typical for an academic or research project website. It prioritizes clarity and information dissemination over elaborate aesthetics. The layout is clean, with a white background and black text, making it easy to read. The use of a distinctive purple-blue from the Magma logo provides a subtle branding element, while standard blue is used for hyperlinks. The page is well-structured with clear headings and numerous illustrative images and diagrams that effectively break down complex technical concepts like SoM and ToM, and showcase experimental results. This visual aid significantly enhances understanding. The overall usability is excellent due to the straightforward navigation and logical flow of information, making it easy for researchers and interested parties to grasp the core concepts and achievements of Magma. While not visually flashy, its professional and organized presentation effectively communicates the project's significance.

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