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Virtualization plays an important role in resource efficiency by optimizing performance, reducing costs, and improving business continuity. IBM PowerVM® provides a secure and scalable server virtualization environment for IBM AIX®, IBM® i, and Linux applications. PowerVM is built on the advanced reliability, availability, and serviceability (RAS) features and leading performance of IBM Power servers. This IBM Redbooks® publication introduces PowerVM virtualization technologies on Power servers. This publication targets clients who are new to Power servers and introduces the available capabilities of the PowerVM platform. This publication includes the following chapters: Chapter 1, "IBM P...
This IBM® Redpaper publication describes the advantages of using IBM Power System AC922 for cognitive solutions, and how it can enhance clients' businesses. In order to optimize the hardware and software, IBM partners with NVIDIA, Mellanox, H2O.ai, SQream, Kinetica, and other prominent companies to design the Power AC922 server, specifically enhanced for the cognitive era. Most of its outstanding hardware features, such as NVIDIA NVLink 2.0 and PCIe 4.0, are described in this publication to illustrate the advantages that clients can realize in comparison with IBM competitors. We also include a brief description about what cognitive computing is, and how to use IBM Watson® Machine Learning ...
This IBM® Redpaper® publication provides a broad understanding of a new architecture of the IBM Power® E1080 (also known as the Power E1080) server that supports IBM AIX®, IBM i, and selected distributions of Linux operating systems. The objective of this paper is to introduce the Power E1080, the most powerful and scalable server of the IBM Power portfolio, and its offerings and relevant functions: Designed to support up to four system nodes and up to 240 IBM Power10TM processor cores The Power E1080 can be initially ordered with a single system node or two system nodes configuration, which provides up to 60 Power10 processor cores with a single node configuration or up to 120 Power10 p...
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.
Europe's critical infrastructure is a key concern to policymakers, NGOs, companies, and citizens today. A 2006 power line failure in northern Germany closed lights in Portugal in a matter of seconds. Several Russian-Ukrainian gas crises shocked politicians, entrepreneurs, and citizens thousands of kilometers away in Germany, France, and Italy. This book argues that present-day infrastructure vulnerabilities resulted from choices of infrastructure builders in the past. It inquires which, and whose, vulnerabilities they perceived, negotiated, prioritized, and inscribed in Europe's critical infrastructure. It does not take 'Europe' for granted, but actively investigates which countries and peoples were historically connected in joint interdependency, and why. In short, this collection unravels the simultaneous historical shaping of infrastructure, common vulnerabilities, and Europe.
This IBM® Redpaper publication explains how IBM Spectrum® Discover integrates with the IBM Watson® Knowledge Catalog (WKC) component of IBM Cloud® Pak for Data (IBM CP4D) to make the enriched catalog content in IBM Spectrum Discover along with the associated data available in WKC and IBM CP4D. From an end-to-end IBM solution point of view, IBM CP4D and WKC provide state-of-the-art data governance, collaboration, and artificial intelligence (AI) and analytics tools, and IBM Spectrum Discover complements these features by adding support for unstructured data on large-scale file and object storage systems on premises and in the cloud. Many organizations face challenges to manage unstructure...
As big data becomes more ubiquitous, businesses are wondering how they can best leverage it to gain insight into their most important business questions. Using machine learning (ML) and deep learning (DL) in big data environments can identify historical patterns and build artificial intelligence (AI) models that can help businesses to improve customer experience, add services and offerings, identify new revenue streams or lines of business (LOBs), and optimize business or manufacturing operations. The power of AI for predictive analytics is being harnessed across all industries, so it is important that businesses familiarize themselves with all of the tools and techniques that are available ...