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  • 1
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : IBM Redbooks | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (32 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: This IBM® Redpaper™ publication is written to assist you in locating the optimal server/workload fit within the IBM Power Systems™ L and IBM OpenPOWER LC product lines. IBM has announced several scale-out servers, and as a partner in the OpenPOWER organization, unique design characteristics that are engineered into the LC line have broadened the suite of available workloads beyond typical client OS hosting. This paper looks at the benefits of the Power Systems L servers and OpenPOWER LC servers, and how they are different, providing unique benefits for Enterprise workloads and use cases.
    Note: Online resource; Title from title page (viewed February 16, 2017)
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : IBM Redbooks | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (64 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: This IBM® Redpaper publication helps the line of business (LOB), data science, and information technology (IT) teams develop an information architecture (IA) for their enterprise artificial intelligence (AI) environment. It describes the challenges that are faced by the three roles when creating and deploying enterprise AI solutions, and how they can collaborate for best results. This publication also highlights the capabilities of the IBM Cognitive Systems and AI solutions: IBM Watson® Machine Learning Community Edition IBM Watson Machine Learning Accelerator (WMLA) IBM PowerAI Vision IBM Watson Machine Learning IBM Watson Studio Local IBM Video Analytics H2O Driverless AI IBM Spectrum® Scale IBM Spectrum Discover This publication examines the challenges through five different use case examples: Artificial vision Natural language processing (NLP) Planning for the future Machine learning (ML) AI teaming and collaboration This publication targets readers from LOBs, data science teams, and IT departments, and anyone that is interested in understanding how to build an IA to support enterprise AI development and deployment.
    Note: Online resource; Title from title page (viewed September 25, 2019)
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
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