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Author: Makenzie Manna
Publisher: IBM Redbooks
ISBN: 0738460923
Category : Computers
Languages : en
Pages : 128
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Book Description
In today's fast-paced, ever-growing digital world, you face various new and complex business problems. To help resolve these problems, enterprises are embedding artificial intelligence (AI) into their mission-critical business processes and applications to help improve operations, optimize performance, personalize the user experience, and differentiate themselves from the competition. Furthermore, the use of AI on the IBM® zSystems platform, where your mission-critical transactions, data, and applications are installed, is a key aspect of modernizing business-critical applications while maintaining strict service-level agreements (SLAs) and security requirements. This colocation of data and AI empowers your enterprise to optimally and easily deploy and infuse AI capabilities into your enterprise workloads with the most recent and relevant data available in real time, which enables a more transparent, accurate, and dependable AI experience. This IBM Redpaper publication introduces and explains AI technologies and hardware optimizations, and demonstrates how to leverage certain capabilities and components to enable AI solutions in business-critical use cases, such as fraud detection and credit risk scoring, on the platform. Real-time inferencing with AI models, a capability that is critical to certain industries and use cases, now can be implemented with optimized performance thanks to innovations like IBM zSystems Integrated Accelerator for AI embedded in the Telum chip within IBM z16TM. This publication describes and demonstrates the implementation and integration of the two end-to-end solutions (fraud detection and credit risk), from developing and training the AI models to deploying the models in an IBM z/OS® V2R5 environment on IBM z16 hardware, and integrating AI functions into an application, for example an IBM z/OS Customer Information Control System (IBM CICS®) application. We describe performance optimization recommendations and considerations when leveraging AI technology on the IBM zSystems platform, including optimizations for micro-batching in IBM Watson® Machine Learning for z/OS. The benefits that are derived from the solutions also are described in detail, including how the open-source AI framework portability of the IBM zSystems platform enables model development and training to be done anywhere, including on IBM zSystems, and enables easy integration to deploy on IBM zSystems for optimal inferencing. Thus, allowing enterprises to uncover insights at the transaction-level while taking advantage of the speed, depth, and securability of the platform. This publication is intended for technical specialists, site reliability engineers, architects, system programmers, and systems engineers. Technologies that are covered include TensorFlow Serving, WMLz, IBM Cloud Pak® for Data (CP4D), IBM z/OS Container Extensions (zCX), IBM CICS, Open Neural Network Exchange (ONNX), and IBM Deep Learning Compiler (zDLC).
Author: Makenzie Manna
Publisher: IBM Redbooks
ISBN: 0738460923
Category : Computers
Languages : en
Pages : 128
Get Book Here
Book Description
In today's fast-paced, ever-growing digital world, you face various new and complex business problems. To help resolve these problems, enterprises are embedding artificial intelligence (AI) into their mission-critical business processes and applications to help improve operations, optimize performance, personalize the user experience, and differentiate themselves from the competition. Furthermore, the use of AI on the IBM® zSystems platform, where your mission-critical transactions, data, and applications are installed, is a key aspect of modernizing business-critical applications while maintaining strict service-level agreements (SLAs) and security requirements. This colocation of data and AI empowers your enterprise to optimally and easily deploy and infuse AI capabilities into your enterprise workloads with the most recent and relevant data available in real time, which enables a more transparent, accurate, and dependable AI experience. This IBM Redpaper publication introduces and explains AI technologies and hardware optimizations, and demonstrates how to leverage certain capabilities and components to enable AI solutions in business-critical use cases, such as fraud detection and credit risk scoring, on the platform. Real-time inferencing with AI models, a capability that is critical to certain industries and use cases, now can be implemented with optimized performance thanks to innovations like IBM zSystems Integrated Accelerator for AI embedded in the Telum chip within IBM z16TM. This publication describes and demonstrates the implementation and integration of the two end-to-end solutions (fraud detection and credit risk), from developing and training the AI models to deploying the models in an IBM z/OS® V2R5 environment on IBM z16 hardware, and integrating AI functions into an application, for example an IBM z/OS Customer Information Control System (IBM CICS®) application. We describe performance optimization recommendations and considerations when leveraging AI technology on the IBM zSystems platform, including optimizations for micro-batching in IBM Watson® Machine Learning for z/OS. The benefits that are derived from the solutions also are described in detail, including how the open-source AI framework portability of the IBM zSystems platform enables model development and training to be done anywhere, including on IBM zSystems, and enables easy integration to deploy on IBM zSystems for optimal inferencing. Thus, allowing enterprises to uncover insights at the transaction-level while taking advantage of the speed, depth, and securability of the platform. This publication is intended for technical specialists, site reliability engineers, architects, system programmers, and systems engineers. Technologies that are covered include TensorFlow Serving, WMLz, IBM Cloud Pak® for Data (CP4D), IBM z/OS Container Extensions (zCX), IBM CICS, Open Neural Network Exchange (ONNX), and IBM Deep Learning Compiler (zDLC).
Author: Lydia Parziale
Publisher: IBM Redbooks
ISBN: 0738458988
Category : Computers
Languages : en
Pages : 80
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Book Description
LinuxONE® is a hardware system that is designed to support and use the Linux operating system based on the value of its unique underlying architecture. LinuxONE can be used within a private and multi-cloud environment to support a range of workloads and service various needs. On LinuxONE, security is built into the hardware and software. This IBM® Redpaper® publication gives a broad understanding of how to use the various security features that make the most of and complement the LinuxONE hardware security features, including the following examples: Hardware accelerated encryption of data, which is delivered with near-zero overhead by the on-chip Central Processor Assist for Cryptographic Function (CPACF) and a dedicated Crypto Express adapter. Virtualization and industry-leading isolation capabilities with PR/SM, EAL 5+ LPARs, DPM, KVM, and IBM z/VM®. The IBM Secure Service Container technology, which provides workload isolation, restricted administrator access, and tamper protection against internal threats, including from systems administrators. Other technologies that use LinuxONE security capabilities and practical use cases for these technologies. This publication was written for IT executives, architects, specialists, security administrators, and others who consider security for LinuxONE.
Author: Ted Schadler
Publisher: Greenleaf Book Group
ISBN: 0991361016
Category : Business & Economics
Languages : en
Pages : 240
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Book Description
Mobile has reprogrammed your customers’ brains. Your customers now turn to their smartphones for everything. What’s tomorrow’s weather? Is the flight on time? Where’s the nearest store, and is this product cheaper there? Whatever the question, the answer is on the phone. This Pavlovian response is the mobile mind shift — the expectation that I can get what I want, anytime, in my immediate context. Your new battleground for customers is this mobile moment — the instant in which your customer is seeking an answer. If you’re there for them, they’ll love you; if you’re not, you’ll lose their business. Both entrepreneurial companies like Dropbox and huge corporations like Nestlé are winning in that mobile moment. Are you? Based on 200 interviews with entrepreneurs and major companies across the globe, The Mobile Mind Shift is the first book to explain how you can exploit mobile moments. You’ll learn how to: • Find your customer’s most powerful mobile moments with a mobile moment audit. • Master the IDEA Cycle, the business discipline for exploiting mobile. Align your business and technology teams in four steps: Identify, Design, Engineer, Analyze. • Manufacture mobile moments as Krispy Kreme does — it sends a push notification when hot doughnuts are ready near you. Result: 500,000 app downloads, followed by a double-digit increase in same-store sales. • Turn one-time product sales into ongoing services and engagement, as the Nest thermostat does. And master new business models, as Philips and Uber do. Find ways to charge more and create indelible customer loyalty. • Transform your technology into systems of engagement. Engineer your business and technology systems to meet the ever-expanding demands of mobile. It’s how Dish Network not only increased the efficiency of its installers but also created new on-the-spot upsell opportunities. Mobile is rapidly shifting your customers into a new way of thinking. You’ll need your own mobile mind shift to respond.
Author: Robert Kruse
Publisher: Pearson Education India
ISBN: 9788177584233
Category :
Languages : en
Pages : 630
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Book Description
Author: Vincenzo Piuri
Publisher: Academic Press
ISBN: 0128222263
Category : Computers
Languages : en
Pages : 306
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Book Description
Trends in Deep Learning Methodologies: Algorithms, Applications, and Systems covers deep learning approaches such as neural networks, deep belief networks, recurrent neural networks, convolutional neural networks, deep auto-encoder, and deep generative networks, which have emerged as powerful computational models. Chapters elaborate on these models which have shown significant success in dealing with massive data for a large number of applications, given their capacity to extract complex hidden features and learn efficient representation in unsupervised settings. Chapters investigate deep learning-based algorithms in a variety of application, including biomedical and health informatics, computer vision, image processing, and more. In recent years, many powerful algorithms have been developed for matching patterns in data and making predictions about future events. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. Deep learning methods can deal with multiple levels of representation in which the system learns to abstract higher level representations of raw data. Earlier, it was a common requirement to have a domain expert to develop a specific model for each specific application, however, recent advancements in representation learning algorithms allow researchers across various subject domains to automatically learn the patterns and representation of the given data for the development of specific models.
Author: Jacques Pitrat
Publisher: John Wiley & Sons
ISBN: 1118617843
Category : Technology & Engineering
Languages : en
Pages : 279
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Book Description
It is almost universally agreed that consciousness and possession of a conscience are essential characteristics of human intelligence. While some believe it to be impossible to create artificial beings possessing these traits, and conclude that ultimate major goal of Artificial Intelligence is hopeless, this book demonstrates that not only is it possible to create entities with capabilities in both areas, but that they demonstrate them in ways different from our own, thereby showing a new kind of consciousness. This latter characteristic affords such entities performance beyond the reach of humans, not for lack of intelligence, but because human intelligence depends on networks of neurons which impose processing restrictions which do not apply to computers. At the beginning of the investigation of the creation of an artificial being, the main goal was not to study the possibility of whether a conscious machine would possess a conscience. However, experimental data indicate that many characteristics implemented to improve efficiency in such systems are linked to these capacities. This implies that when they are present it is because they are essential to the desired performance improvement. Moreover, since the goal is not to imitate human behavior, some of these structural characteristics are different from those displayed by the neurons of the human brain - suggesting that we are at the threshold of a new scientific field, artificial cognition, which formalizes methods for giving cognitive capabilities to artificial entities through the full use of the computational power of machines.
Author: Liran Tal
Publisher: Lulu.com
ISBN: 1365698556
Category : Computers
Languages : en
Pages : 112
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Book Description
Hands-on and abundant with source code for a practical guide to Securing Node.js web applications. This book is intended to be a hands-on thorough guide for securing web applications based on Node.js and the ExpressJS web application framework. Many of the concepts, tools and practices in this book are primarily based on open source libraries and the author leverages these projects and highlights them. The main objective of the book is to equip the reader with practical solutions to real world problems, and so this book is heavily saturated with source code examples as well as a high level description of the risks involved with any security topic, and the practical solution to prevent or mitigate it.
Author: Pierre Bessiere
Publisher: CRC Press
ISBN: 1439880336
Category : Business & Economics
Languages : ru
Pages : 380
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Book Description
Probability as an Alternative to Boolean LogicWhile logic is the mathematical foundation of rational reasoning and the fundamental principle of computing, it is restricted to problems where information is both complete and certain. However, many real-world problems, from financial investments to email filtering, are incomplete or uncertain in natur
Author: Hatice Gunes
Publisher: Frontiers Media SA
ISBN: 288963454X
Category :
Languages : en
Pages : 185
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Book Description
Designing robots with socio-emotional skills is a challenging research topic still in its infancy. These skills are important for robots to be able to provide not only physical, but also social support to human users, and to engage in and sustain long-term interactions with them in a variety of application domains that require human-robot interaction, including healthcare, education, entertainment, manufacturing, and many others. The availability of commercial robotic platforms and developments in collaborative academic research provide us a positive outlook, however, the capabilities of current social robots are quite limited. The main challenge is understanding the underlying mechanisms of the humans in responding to and interacting with real life situations, and how to model these mechanisms for the embodiment of naturalistic, human-inspired behaviors via robots. To address this challenge successfully requires an understanding of the essential components of social interaction including nonverbal behavioral cues such as interpersonal distance, body position, body posture, arm and hand gestures, head and facial gestures, gaze, silences, vocal outbursts and their dynamics. To create truly intelligent social robots, these nonverbal cues need to be interpreted to form an understanding of the higher level phenomena including first-impression formation, social roles, interpersonal relationships, focus of attention, synchrony, affective states, emotions, and personality, and in turn defining optimal protocols and behaviors to express these phenomena through robotic platforms in an appropriate and timely manner. Achieving this goal requires the fields of psychology, nonverbal behavior, vision, social signal processing, affective computing, and HRI to constantly interact with one another. This Research Topic aims to foster such interactions and collaborations by bringing together the latest works and developments from across a range of research groups and disciplines working in these fields. The Research Topic is a collection of 14 articles that span across five research themes. Three articles co-authored by Terada and Takeuchi, Jung et al., and Kennedy et al. explore the design of “social and affective cues” for robots and investigate their effects on human-robot interaction. Mirnig et al., Bremner et al., and Strait et al. investigate people’s “perceptions of robots” in different settings and scenarios, such as when robots make errors. Articles by Lee et al., Leite et al., and Heath et al. investigate the factors that shape “dialogic interaction with robots,” such as interaction context. The articles under the theme “social and affective therapy” by Rouaix et al., Rudovic et al., and Matsuda et al. report on how individuals from clinical populations, such as those with dementia, autism, and other pervasive developmental disorders (PDDs), interact with robots in therapeutic scenarios. Finally, Miklósi et al. and Durantin et al. offer “new perspectives in human-robot interaction” with a focus on reframing social interaction and human-robot relationships. We are excited about sharing this rich collection with the scientific community and about its contributions to the human-robot interaction literature.
Author: Tope Omitola
Publisher: Morgan & Claypool Publishers
ISBN: 1627053999
Category : Computers
Languages : en
Pages : 156
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Book Description
The past ten years have seen a rapid growth in the numbers of people signing up to use Web-based social networks (hundreds of millions of new members are now joining the main services each year) with a large amount of content being shared on these networks (tens of billions of content items are shared each month). With this growth in usage and data being generated, there are many opportunities to discover the knowledge that is often inherent but somewhat hidden in these networks. Web mining techniques are being used to derive this hidden knowledge. In addition, the Semantic Web, including the Linked Data initiative to connect previously disconnected datasets, is making it possible to connect data from across various social spaces through common representations and agreed upon terms for people, content items, etc. In this book, we detail some current research being carried out to semantically represent the implicit and explicit structures on the Social Web, along with the techniques being used to elicit relevant knowledge from these structures, and we present the mechanisms that can be used to intelligently mesh these semantic representations with intelligent knowledge discovery processes. We begin this book with an overview of the origins of the Web, and then show how web intelligence can be derived from a combination of web and Social Web mining. We give an overview of the Social and Semantic Webs, followed by a description of the combined Social Semantic Web (along with some of the possibilities it affords), and the various semantic representation formats for the data created in social networks and on social media sites. Provenance and provenance mining is an important aspect here, especially when data is combined from multiple services. We will expand on the subject of provenance and especially its importance in relation to social data. We will describe extensions to social semantic vocabularies specifically designed for community mining purposes (SIOCM). In the last three chapters, we describe how the combination of web intelligence and social semantic data can be used to derive knowledge from the Social Web, starting at the community level (macro), and then moving through group mining (meso) to user profile mining (micro). Table of Contents: Acknowledgments / Grant Aid / Introduction and the Web / Web Mining / The Social Web / The Semantic Web / The Social Semantic Web / Social Semantic Web Mining / Social Semantic Web Mining of Communities / Social Semantic Web Mining of Groups / Social Semantic Web Mining of Users / Conclusions / Bibliography / Authors' Biographies
