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HomeNewsSalesforce Releases xGen-MM Open-source Multimodal AI Models

Salesforce Releases xGen-MM Open-source Multimodal AI Models

Salesforce unveils xGen-MM, an open-source AI model that helps you integrate text and images. This move promotes transparency in AI development environments and fosters collaboration.

Salesforce has introduced xGen-MM, a powerful new AI model, as open-source. By providing public access to these advanced AI tools, Salesforce fosters innovation and promotes a culture of transparency in AI development. This open-source approach helps you build and improve these models, driving the evolution of AI.

xGen-MM has been introduced to handle tasks that require integrating images and text. These models can combine and process these two types of data simultaneously, enabling them to perform complex tasks, such as answering questions that include multiple images. This capability of xGen-MM makes it efficient for a wide range of applications, from healthcare to autonomous systems.

xGen-MM’s capabilities lie in its training on MINT-1T datasets. It is a dataset of enormous data collections comprising a trillion tokens of mixed text and image content. This vast dataset equips the models with a deep understanding of how text and image data interact with each other. The diversity of xGen-MM reaches new levels of performance in multimodal AI.

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Addressing your needs, xGen-MM offers different model variants, such as instruction-tuned and safety-tuned models. The instruction-tuned model follows specific tasks or directions, and the safety-tuned model is designed to minimize unethical outputs. This versatility highlights Salesforce’s dedication to building AI technology that can be used responsibly in real-world scenarios.

Salesforce’s decision to make xGen-MM an open-source marks a shift towards maintaining transparency in AI environments. This move could inspire other companies to adopt similar practices, promoting a more open and collaborative environment. 
As the community embraces xGen-MM, its impact on real-world applications and research will grow significantly. This progress will create new opportunities for future innovations in artificial intelligence technology.

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Analytics Drift
Analytics Drift
Editorial team of Analytics Drift

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