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White papers that describe solutions for artificial intelligence, including related white papers from analysts and partners
This white paper describes the combination of deployment process mining with machine learning to develop a prediction model that eliminates nonvalue-added steps and significantly improves customer time to value.
This paper describes Dell EMC PowerEdge R750xa server performance results submitted to the MLPerf™ Inference v1.0 benchmark. The results indicate that the server delivered optimal performance making it an excellent choice for inference workloads.
This whitepaper describes how Dell Technologies is working with monoDrive to produce high-fidelity simulations using the industry-leading PowerEdge and PowerStore systems.
Dell Technologies has a rich portfolio of hardware platforms that are being used to power ML and DL solutions. This paper showcases two servers from Dell Technologies that are powered by AMD processors and accelerated by NVIDIA GPUs.
A Ready Solution developed by the Dell Technologies AI Innovation Lab partnering with Deep Vision AI and NVIDIA. It uses intelligent video analytics to create safer and smarter environments for retail stores, health care, manufacturing, and other industries.
This technical paper presents the testing results of a SAS Viya workload on the Dell EMC VxFlex system. The Dell EMC VxFlex was utilized as an MPP architecture for the Viya system.
This white paper describes a solution that Dell Technologies has developed with hardware and software partners to make it easier and more cost-effective for retailers to employ new technology to reduce inventory loss at the checkout lane in stores
This white paper describes the design of Domino Data Science Platform on Dell EMC infrastructure. Data scientists must be able to streamline model development to deployment by using an enterprise platform.
Dell Technologies, DataRobot, and Intel deliver an on-premises enterprise artificial intelligence (AI) solution stack to enable organizations to implement AI transformation projects on trusted infrastructure.
This white paper assembles the experience of Canonical, Dell, SUSE, Intel, and Grid Dynamics in designing, building, and supporting machine learning and data science platforms.
This white paper outlines technical considerations and sizing guidance for on-premises enterprise AI platform reference architectures jointly developed by Dell Technologies, Intel, and H2O.ai.
This white paper outlines the technical considerations for deploying an on-premises enterprise data science reference architecture jointly developed by Dell Technologies, Intel, and Iguazio, and optimized for real-world performance and scalability.
A two-part white paper covering the benefits of using the Comet machine learning platform with a Dell EMC AI-enabled infrastructure.