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io.net is advancing its decentralized AI infrastructure by integrating Walrus’ encrypted storage protocol. This collaboration provides developers with a secure way to train and deploy custom models without relying on traditional cloud providers, offering a significant step forward for AI and machine learning (ML) applications.
io.net Partners with Walrus to Enhance Decentralized AI
io.net, a decentralized cloud provider, has announced a partnership with Walrus, a Sui-based storage protocol. This integration is designed to offer a robust infrastructure for AI/ML developers, enabling secure storage and efficient computation on a decentralized network.
The partnership allows developers to store proprietary models securely on Walrus’ tamper-proof decentralized storage network. Simultaneously, they can leverage io.net’s globally distributed GPU clusters for training and inference tasks, ensuring privacy and affordability in AI development.
“Partnering with Walrus unlocks a game-changing opportunity for AI/ML teams. By integrating Walrus’s secure, decentralized storage with io.net’s distributed compute, we’re empowering users to deploy models affordably and privately, paving the way for a new era of decentralized AI innovation,” said Tausif Ahmed, Chief Business Development Officer at io.net.
Key Features of the Integration
The io.net and Walrus partnership introduces a set of innovative features that address the challenges posed by centralized cloud services. These features aim to simplify AI/ML development while ensuring security and cost-effectiveness.
- Bring Your Own Model Framework: This framework allows developers to deploy custom AI models without being restricted to pre-approved options, offering greater flexibility and control.
- Private Compute Execution: Encrypted models stored on Walrus can seamlessly integrate with io.net’s GPU clusters for processing, all while remaining cryptographically secured throughout the execution process.
- Pay-As-You-Go Model: Developers can avoid high upfront costs and predatory pricing structures, making AI development more accessible to teams with limited budgets.
Addressing Centralized Cloud Limitations
The integration comes at a critical time as the demand for AI/ML infrastructure continues to grow. Many developers rely on centralized cloud providers, which often introduce challenges such as high costs, data ownership concerns, and censorship risks. By decentralizing both storage and computation, the io.net-Walrus partnership offers a credible alternative that aligns with the principles of Web3 while prioritizing developer needs.
Decentralized solutions like this aim to eliminate the bottlenecks associated with traditional cloud services, providing a more sustainable and secure path for AI innovation. With this collaboration, developers gain access to tools that not only reduce costs but also enhance privacy and data sovereignty.
As the demand for scalable and secure AI/ML solutions continues to rise, partnerships like io.net and Walrus stand to reshape the landscape of decentralized technology, empowering developers and fostering innovation in the Web3 ecosystem.
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