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Optimized Inferencing and Integration with AI on IBM zSystems: Introduction, Methodology, and Use Cases

Optimized Inferencing and Integration with AI on IBM zSystems: Introduction, Methodology, and Use Cases PDF Author: Makenzie Manna
Publisher: IBM Redbooks
ISBN: 0738460923
Category : Computers
Languages : en
Pages : 128

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).

Optimized Inferencing and Integration with AI on IBM zSystems: Introduction, Methodology, and Use Cases

Optimized Inferencing and Integration with AI on IBM zSystems: Introduction, Methodology, and Use Cases PDF Author: Makenzie Manna
Publisher: IBM Redbooks
ISBN: 0738460923
Category : Computers
Languages : en
Pages : 128

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).

The AI-Powered Enterprise

The AI-Powered Enterprise PDF Author: Seth Earley
Publisher: LifeTree Media
ISBN: 1928055524
Category : Business & Economics
Languages : en
Pages : 203

Book Description
Learn how to develop and employ an ontology, the secret weapon for successfully using artificial intelligence to create a powerful competitive advantage in your business. The AI-Powered Enterprise examines two fundamental questions: First, how will the future be different as a result of artificial intelligence? And second, what must companies do to stake their claim on that future? When the Web came along in the mid-90s, it transformed the behavior of customers and remade whole industries. Now, as part of its promise to bring revolutionary change in untold ways to human activity, artificial intelligence—AI—is about to create another complete transformation in how companies create and deliver value to customers. But despite the billions spent so far on bots and other tools, AI continues to stumble. Why can't it magically use all the data organizations generate to make them run faster and better? Because something is missing. AI works only when it understands the soul of the business. An ontology is a holistic digital model of every piece of information that matters to the business, from processes to products to people, and it's what makes the difference between the promise of AI and delivering on that promise. Business leaders who want to catch the AI wave—rather than be crushed by it—need to read The AI-Powered Enterprise. The book is the first to combine a sophisticated explanation of how AI works with a practical approach to applying AI to the problems of business, from customer experience to business operations to product development.

Trust in Computer Systems and the Cloud

Trust in Computer Systems and the Cloud PDF Author: Mike Bursell
Publisher: John Wiley & Sons
ISBN: 1119692318
Category : Computers
Languages : en
Pages : 352

Book Description
Learn to analyze and measure risk by exploring the nature of trust and its application to cybersecurity Trust in Computer Systems and the Cloud delivers an insightful and practical new take on what it means to trust in the context of computer and network security and the impact on the emerging field of Confidential Computing. Author Mike Bursell’s experience, ranging from Chief Security Architect at Red Hat to CEO at a Confidential Computing start-up grounds the reader in fundamental concepts of trust and related ideas before discussing the more sophisticated applications of these concepts to various areas in computing. The book demonstrates in the importance of understanding and quantifying risk and draws on the social and computer sciences to explain hardware and software security, complex systems, and open source communities. It takes a detailed look at the impact of Confidential Computing on security, trust and risk and also describes the emerging concept of trust domains, which provide an alternative to standard layered security. Foundational definitions of trust from sociology and other social sciences, how they evolved, and what modern concepts of trust mean to computer professionals A comprehensive examination of the importance of systems, from open-source communities to HSMs, TPMs, and Confidential Computing with TEEs. A thorough exploration of trust domains, including explorations of communities of practice, the centralization of control and policies, and monitoring Perfect for security architects at the CISSP level or higher, Trust in Computer Systems and the Cloud is also an indispensable addition to the libraries of system architects, security system engineers, and master’s students in software architecture and security.

The Mobile Mind Shift

The Mobile Mind Shift PDF Author: Ted Schadler
Publisher: Greenleaf Book Group
ISBN: 0991361016
Category : Business & Economics
Languages : en
Pages : 335

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.

Rogue Code

Rogue Code PDF Author: Mark Russinovich
Publisher: Macmillan
ISBN: 1250035376
Category : Fiction
Languages : en
Pages : 398

Book Description
Investigating a possible breach in the New York Stock Exchange, cyber security expert Jeff Aiken discovers that high-ranking officials both knew about the breach and allowed millions to be stolen, a finding that causes Jeff to be violently targeted by powerful enemies who would upend the U.S. economy. 40,000 first printing.

Trends in Deep Learning Methodologies

Trends in Deep Learning Methodologies PDF Author: Vincenzo Piuri
Publisher: Academic Press
ISBN: 0128232684
Category : Computers
Languages : en
Pages : 308

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. Provides insights into the theory, algorithms, implementation and the application of deep learning techniques Covers a wide range of applications of deep learning across smart healthcare and smart engineering Investigates the development of new models and how they can be exploited to find appropriate solutions

Essential Node.js Security

Essential Node.js Security PDF Author: Liran Tal
Publisher: Lulu.com
ISBN: 1365698556
Category :
Languages : en
Pages : 112

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.

Data Structures and Program Design in C

Data Structures and Program Design in C PDF Author: Robert Kruse
Publisher: Pearson Education India
ISBN: 9788177584233
Category :
Languages : en
Pages : 630

Book Description


Artificial Beings

Artificial Beings PDF Author: Jacques Pitrat
Publisher: John Wiley & Sons
ISBN: 1118617843
Category : Technology & Engineering
Languages : en
Pages : 279

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.

Dependable Embedded Systems

Dependable Embedded Systems PDF Author: Jörg Henkel
Publisher: Springer Nature
ISBN: 303052017X
Category : Technology & Engineering
Languages : en
Pages : 606

Book Description
This Open Access book introduces readers to many new techniques for enhancing and optimizing reliability in embedded systems, which have emerged particularly within the last five years. This book introduces the most prominent reliability concerns from today’s points of view and roughly recapitulates the progress in the community so far. Unlike other books that focus on a single abstraction level such circuit level or system level alone, the focus of this book is to deal with the different reliability challenges across different levels starting from the physical level all the way to the system level (cross-layer approaches). The book aims at demonstrating how new hardware/software co-design solution can be proposed to ef-fectively mitigate reliability degradation such as transistor aging, processor variation, temperature effects, soft errors, etc. Provides readers with latest insights into novel, cross-layer methods and models with respect to dependability of embedded systems; Describes cross-layer approaches that can leverage reliability through techniques that are pro-actively designed with respect to techniques at other layers; Explains run-time adaptation and concepts/means of self-organization, in order to achieve error resiliency in complex, future many core systems.