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Scaling AI? Start with the Right Storage Architecture

  • 1.  Scaling AI? Start with the Right Storage Architecture

    Posted 6 hours ago

    AI workloads are evolving fast-from traditional ML pipelines to complex generative models. But one thing remains constant: data growth. And the ability to store, access, and manage massive volumes of unstructured data efficiently is now a critical architectural decision.

    In our latest IBM blog, we unpack why Object Storage is the backbone of scalable AI-and how it fits into modern data lakehouse and AI stack designs.

    🔍 Key takeaways for technical teams:

    • Native support for unstructured data at petabyte scale
    • Seamless integration with query engines like Presto, Spark, and watsonx.data
    • Tiered storage for cost optimization without sacrificing performance
    • Immutable data retention and quantum-safe encryption for compliance
    • Proven 2x price-performance gains vs. traditional cloud storage

    Whether you're building out a lakehouse, optimizing AI pipelines, or architecting for multi-cloud, this blog is a must-read.

    📘 Read the full playbook: The object storage playbook for scalable AI: Use cases and best practices | IBM



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    Danielle Kingberg
    Sr. GTM Product Manager, IBM Cloud Object Storage
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