AI Research Lab Opengradient leveraged the Walrus Data Storage protocol to create distributed AI agents.
Centralization is one of the main concerns of AI systems, so multiple companies are turning to blockchain to address blockchain. On Wednesday, June 25th, OpenGradient announced its integration with walruses to bring distributed AI to the SUI network (SUI).
OpenGradient uses Walrus’ distributed storage network to build and run distributed AI agents. According to the team, the integration can host over 100 AI models across dozens of ecosystems.
Ultimately, the goal of the platform is to make decentralized AI a reality. Matthew Wang, co-founder and CEO of OpenGradient, explained to users the benefits of controlling your AI model. Specifically, the model is private, cheaper to execute and more transparent.
“AI does not belong to a handful of large tech companies. It belongs to the user and has always been. It is our mission to make this idea come true, giving both veteran AI developers and everyday consumers the ability to create, modify and own their own AI models.”
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AI models require distributed data: Walrus Foundation
AI models require access to a large amount of data. This makes distributed storage more attractive. Rebecca Simmonds, managing executive at the Walrus Foundation, highlighted why AI Solutions developers need a storage platform like Walrus.
“The only option available is the privacy and control risks inherent in centralized architectures, making it nearly impossible to build a truly distributed model. Integration with open gradients allows us to meet that needs and provide a distributed storage solution for users to control their data.”
Thanks to the open storage protocol, users can see exactly which training data will enter the AI model. According to OpenGradient, users and developers can now leverage Walrus data storage to build and train their own models.
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