Infinia WhitepaperDDN Infinia gives fluid control of data from edge to core and core to cloud, while maximizing the capabilities of the underlying infrastructure, including storage, network and compute.
View Resource Large Language ModelsIn this white paper, we take a platform approach to accelerate LLMs and show how GPU,
memory, and storage collectively contribute to overall LLM performance.
View Resource The AI Data FactoryData monetization is now led by market-driven business priorities and outcomes,
expressed as measurable results that affect the bottom line.
View Resource Streamlining AI Data ManagementFor supreme AI data management, the AI data lifecycle needs a clear, continuous flow, both for training of AI models, and for applying AI models to real time decision making.
View Resource How to Build an AI Center of ExcellenceOrganizations need to adopt a disciplined approach to implementing and measuring the outcomes of AI projects.
View Resource AI Engineering: A New DisciplineAI engineering is an emerging discipline that focuses on applying tools, systems, and processes to enable AI to perform effectively.
View Resource NVIDIA DGX SuperPOD AI400X2The NVIDIA DGX SuperPOD™ is a first-of-its-kind artificial intelligence (AI) supercomputing infrastructure.
View Resource NVIDIA DGX BasePOD A100The DDN A³I scalable architecture integrates DGX A100 systems with DDN AI shared parallel file storage appliances and delivers fully optimized end-to-end AI, Analytics and HPC workflow.
View Resource Accelerate Artificial Intelligence Initiatives with DDN and NVIDIA at Any ScaleData now plays such a prominent role in determining business success that 98% of organizations surveyed by ESG are in some phase of data-driven digital transformation.
View Resource Evaluating Infrastructure Options for Enterprise DevelopmentAlthough the promise and attraction of AI is well appreciated by IT and business decision-makers alike, it’s far less clear how organizations should begin their journey to enterprise-class AI.
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