Introducing the i-Code Project
The i-Code project is an impressive and ambitious initiative aimed at creating a comprehensive and adaptable Artificial Intelligence (AI) framework that integrates multiple modalities. In this context, “i” represents integrative multimodal learning, highlighting the project's focus on combining various forms of data for enhanced AI capabilities.
Multimodal Foundation Models
At the heart of the i-Code project are various multimodal foundation models that facilitate this integrative approach:
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i-Code V1: This is an integrative and composable multimodal learning framework that was presented at the AAAI 2023 conference. Learn more about it here.
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i-Code V2: Building on the first version, i-Code V2 offers an autoregressive generation framework that can process data across vision, language, and speech. This reflects an advancement in AI's ability to generate and understand diverse data types. Read the paper here.
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i-Code V3 (CoDi): Known as CoDi, this version introduces "Any-to-Any Generation" through a method called Composable Diffusion. It opens up new possibilities for AI to synthesize data from varied inputs. Find the paper here.
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i-Code Studio: This component is a configurable and composable framework designed for broader integrative AI purposes. It serves as a versatile base for developing AI applications. Access the paper here.
Multimodal Document Intelligence
Another significant aspect of the i-Code project is its contribution to multimodal document intelligence. The i-Code Doc model, also referred to as UDOP, is engineered to unify vision, text, and layout for universal document processing. This was highlighted at the CVPR 2023 event. View the paper here.
Knowledge-Based Visual Question Answering
The MM-Reasoner is a framework developed under the i-Code project that caters to knowledge-based visual question answering. This model incorporates multiple modalities and awareness of knowledge entities to enhance the accuracy and relevance of AI responses. This innovation was part of the EMNLP 2023 Findings.
Contributing to the Project
The i-Code project is open for contributions from the community. Contributors must agree to a Contributor License Agreement (CLA), ensuring they have the rights to their contributions and grant those rights to the project. A CLA bot helps streamline this process by guiding applicants through what’s required.
Furthermore, the project operates under the Microsoft Open Source Code of Conduct, emphasizing a respectful and inclusive environment for all contributors.
Trademarks and Usage
The project may use trademarks or logos of Microsoft, which should comply with Microsoft's Trademark & Brand Guidelines. It is essential to ensure that any modifications do not misrepresent sponsorship or endorsements by Microsoft.
In summary, the i-Code project leads the way in developing integrative AI systems that effectively leverage multimodal data, providing significant innovations in AI learning and application potential. The project's openness to community involvement further bolsters its development and reach.