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@chorang
Today, we learned about the future of AI 1️⃣ AI’s Expanding Data Needs AI is rapidly evolving, with a projected market value of $1,278 billion by 2028. However, its growth drives massive data demands, increasing power consumption and straining existing storage systems. 2️⃣ Challenges in Decentralized Storage Current decentralized storage networks struggle with scalability, speed, and security. AI requires vast, real-time data access, but many systems lack efficiency and proper verification mechanisms, raising concerns about data integrity. 3️⃣ The Future of AI-Ready Storage Decentralized storage must prioritize scalability, security, and interoperability. Blockchain and edge computing can enhance storage efficiency, ensuring AI operates seamlessly across various platforms while maintaining data integrity.
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@project7
NodeShift can be a great example for this! https://nodeshift.com/blog/nodeshift-integrates-with-storj-to-expand-decentralized-hot-storage-and-compute-solutions tl;dr: * NodeShift provides virtual machines (VMs) and GPUs for intensive computing tasks, such as AI model training. * Storj offers secure, cost-effective storage compatible with S3, a widely used online file storage system. * Integration allows NodeShift’s computing resources to connect seamlessly with Storj’s storage via S3. * Users can configure a VM or GPU on NodeShift and link it to Storj’s storage effortlessly. * For AI training, data can be quickly retrieved from Storj, processed on NodeShift, and saved back without issues.
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