Armonk, NY (May 8, 2025) \u2013 IBM is pleased to announce the IBM z17<\/a>, the next generation of the company\u2019s iconic mainframe, fully engineered with AI capabilities across hardware, software, and systems operations. Powered by the new IBM Telum\u00ae II processor, IBM z17 expands the system\u2019s capabilities beyond transactional AI capabilities to enable new workloads.<\/p>\n IBM Z is built to redefine AI at scale, positioning enterprises to score 100% of their transactions in real-time.[1<\/a>]<\/sup> z17 enables businesses to drive innovation and do more, including the ability to process 50 percent more AI inference operations per day than z16.[2<\/a>]<\/sup> The new IBM z17 is built to drive business value across industries with a wide range of more than 250 AI use cases, such as mitigating loan risk, managing chatbot services, supporting medical image analysis or impeding retail crime, among others.<\/p>\n IBM z17 is the culmination of five years of design and development which included the filing of more than 300 patent applications filed with the US Patent and Trademark Office. Designed with the direct input of more than 100 clients and in close collaboration with IBM Research and Software teams; the new system introduces multi-model AI capabilities, new security features to protect data, and tools that leverage AI for improving system usability and management:<\/p>\n \u201cThe industry is quickly learning that AI will only be as valuable as the infrastructure it runs on,\u201d said Ross Mauri, general manager of IBM Z and LinuxONE, IBM. \u201cWith z17, we\u2019re bringing AI to the core of the enterprise with the software, processing power, and storage to make AI operational quickly. Additionally, organizations can put their vast, untapped stores of enterprise data to work with AI in a secured, cost-effective way.\u201d<\/p>\n Fully Integrated Across Hardware and Software<\/strong><\/p>\n IBM z17 is a system designed from the ground up to fully integrate into hybrid environments by tightly joining hardware innovations, software capabilities for AI, and rich support for open-standards and tooling. This enables differentiated performance and reliability while reimagining how developers and systems operators engage with and manage IBM Z, including:<\/p>\n Built for Resiliency: Security and Cyber Defense at the Core<\/strong><\/p>\n IBM z17 furthers the platform\u2019s history of strong security and resiliency capabilities. New developments in AI have enabled the deployment of added intelligence across this ever-growing area of importance for clients as new threats appear every day. This includes several new capabilities, including:<\/p>\n IBM Extends AI-Enabled Support to IBM z17<\/strong><\/p>\n IBM\u2019s tailored, comprehensive support experience helps IBM Z clients meet demands beyond traditional maintenance. Delivered by IBM Technology Lifecycle Services, IBM Support for z17 helps clients optimize their environments for peak performance to address risk and disruptions for mission-critical operations. IBM\u2019s AI processes streamline incident remediation and help improve case resolution time, built on IBM watsonx, now support IBM Z systems.<\/p>\n IBM Delivers Secured and Agile Storage<\/strong><\/p>\n IBM Storage DS8000 plays a key role as an integrated storage solution for IBM Z. The latest generation of IBM Storage DS8000 (10th<\/sup> Generation<\/a>) is designed to harness the full power of IBM z17, providing organizations access to critical workloads, consistent and optimized data performance, and a modular architecture to adopt the latest IBM research-backed technologies to fuel business growth while monetizing data. Together, IBM Z and IBM Storage offer a modern infrastructure delivering a secured and agile platform for mission-critical workloads.<\/p>\n Availability<\/strong><\/p>\n IBM z17 will be generally available June 18, 2025 For more information, visit IBM.com\/z17<\/a>. The IBM Spyre\u2122 Accelerator is expected to be available starting in Q4 2025.<\/p>\n Statements regarding IBM\u2019s future direction and intent are subject to change or withdrawal without notice, and represent goals and objectives only.<\/em><\/p>\n 1. Claim \u2013 Since the introduction of IBM z16 in 2022, IBM Z mainframes have been able to support AI inferencing directly in the mainframe, making it possible to score 100% of real-time transactions even in high-volume production environments.<\/em><\/p>\n Source \u2013 Celent report: \u201cMitigating Fraud in The AI Age<\/a>\u201d by Neil Katkov, 04\/08\/2025, commissioned by IBM<\/em><\/p>\n 2. Claim \u2013 The percentage difference between IBM z17, that processes up to 450 billion inference operations per day with 1 ms response time using a Credit Card Fraud Detection Deep Learning model, and IBM z16, process up to 300 billion inference requests per day with 1ms response time using a Credit Card Fraud Detection model. For IBM z17 up to 450 billion inferences operations per day.<\/em><\/p>\n For z17 performance result is extrapolated from IBM\u00ae internal tests running on IBM Systems Hardware of machine type 9175. The benchmark was executed with 1 thread performing local inference operations using a LSTM based synthetic Credit Card Fraud Detection model (https:\/\/github.com\/IBM\/ai-on-z-fraud-detection<\/a>) to exploit the integrated Accelerator for AI. A batch size of 160 was used. IBM Systems Hardware configuration: 1 LPAR running Red Hat\u00ae Enterprise Linux\u00ae 9.4 with 6 IFLs (SMT), 128 GB memory. 1 LPAR with 2 CPs, 4 zIIPs and 256 GB memory running IBM z\/OS\u00ae 3.1 with IBM z\/OS Container Extensions (zCX) feature. Results may vary. For IBM z16, performance result is extrapolated from IBM internal tests running local inference operations in an IBM z16 LPAR with 48 IFLs and 128 GB memory on Ubuntu 20.04 (SMT mode) using a synthetic credit card fraud detection model (https:\/\/github.com\/IBM\/ai-on-z-fraud-detection<\/a>) exploiting the IBM Integrated Accelerator for AI. The benchmark was running with 8 parallel threads each pinned to the first core of a different chip. The lscpu command was used to identify the core-chip topology. A batch size of 128 inference operations was used. Results were also reproduced using a z\/OS V2R4 LPAR with 24 CPs and 256GB memory on IBM z16. The same credit card fraud detection model was used. The benchmark was executed with a single thread performing inference operations. A batch size of 128 inference operations was used. Results may vary.<\/em><\/p>\n IBM (NYSE: IBM)<\/em> is a leading provider of global hybrid cloud and AI, and consulting expertise. We help clients in more than 175 countries capitalize on insights from their data, streamline business processes, reduce costs and gain the competitive edge in their industries. Thousands of government and corporate entities in critical infrastructure areas such as financial services, telecommunications and healthcare rely on IBM\u2019s hybrid cloud platform and Red Hat OpenShift to affect their digital transformations quickly, efficiently and securely. IBM\u2019s breakthrough innovations in AI, quantum computing, industry-specific cloud solutions and consulting deliver open and flexible options to our clients. All of this is backed by IBM\u2019s long-standing commitment to trust, transparency, responsibility, inclusivity and service. Visit www.ibm.com<\/a> for more information.<\/p>\n Source: IBM<\/i><\/p>\n Tags: Artificial Intelligence (AI)<\/a>, IBM<\/a>, industry first<\/a> <\/p>\n","protected":false},"excerpt":{"rendered":" New Innovations Unlock Capabilities for Enterprise-Scale AI, Including Large Language Models and Generative AI; User Experience Reimagined via new Assistants and Agents Armonk, NY (May 8, 2025) \u2013 IBM is pleased to announce the...<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[],"tags":[1],"jetpack_featured_media_url":"","_links":{"self":[{"href":"https:\/\/blog.lifeinsurance-orleans.ca\/index.php\/wp-json\/wp\/v2\/posts\/23612"}],"collection":[{"href":"https:\/\/blog.lifeinsurance-orleans.ca\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blog.lifeinsurance-orleans.ca\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blog.lifeinsurance-orleans.ca\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/blog.lifeinsurance-orleans.ca\/index.php\/wp-json\/wp\/v2\/comments?post=23612"}],"version-history":[{"count":0,"href":"https:\/\/blog.lifeinsurance-orleans.ca\/index.php\/wp-json\/wp\/v2\/posts\/23612\/revisions"}],"wp:attachment":[{"href":"https:\/\/blog.lifeinsurance-orleans.ca\/index.php\/wp-json\/wp\/v2\/media?parent=23612"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blog.lifeinsurance-orleans.ca\/index.php\/wp-json\/wp\/v2\/categories?post=23612"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blog.lifeinsurance-orleans.ca\/index.php\/wp-json\/wp\/v2\/tags?post=23612"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}\n
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Notes<\/h4>\n
Disclaimer<\/b><\/h4>\n
About IBM<\/b><\/h4>\n