IBM Accelerates Enterprise AI for Clients with New Capabilities on IBM Z
Sept. 26, 2023 — Today, IBM is excited to unveil a new suite of AI offerings for IBM Z that are designed to help clients improve business outcomes by speeding the implementation of enterprise AI on IBM Z across a wide variety of use cases and industries.
IBM is bringing artificial intelligence (AI) to emerging use cases that clients have begun exploring, such as enhancing the accuracy of insurance policy recommendations, increasing the accuracy and timeliness of anti-money laundering controls, and further reducing risk exposure for financial services companies.
The new offerings are designed to help accelerate the adoption of popular AI frameworks and tooling. The Company is also announcing an enhanced Machine Learning for z/OS and advanced intelligence and operational improvements with the latest IBM z/OS operating system.
IBM’s rich AI offerings—coupled with low-latency inferencing that leverages the IBM Telum on-chip AI accelerator—are designed to help clients integrate AI workloads into their most mission-critical business applications running on IBM Z and meet their throughput SLAs.
- AI Toolkit for IBM Z and LinuxONE: Expected to be generally available in Q4, the toolkit is anticipated to support popular industry-standard open-source frameworks—such as IBM Z Accelerated for TensorFlow, IBM Z Accelerated for TensorFlow Serving, IBM Z Accelerated for Snap ML and others—so that businesses can start implementing trustworthy AI.
- Python AI Toolkit for IBM z/OS: This enhanced toolkit is a library of open-source Python software to support AI and machine learning workloads that adheres to IBM Security and Privacy by Design practices. Clients can now leverage zIIP-eligible packages with Python AI Toolkit for IBM z/OS and IBM Open Enterprise SDK for Python 3.11 to embed AI into their applications.
To help data scientists, developers and IT teams implement AI together, these toolkits for Z are designed to support clients as they aim to connect mainframe data and applications to open-source frameworks and packages. These tools include frameworks and libraries that are optimized and supported for IBM Z, and they are built to allow developers to start implementing trustworthy AI capabilities on z/OS. Supported by the same underpinnings for IBM watsonx.ai that empower data scientists and developers to build, run and manage machine learning models, these toolkits will evolve over time to become an integral part of the IBM watsonx platform.
- Machine Learning for IBM z/OS – Enterprise and Core Editions: The enhanced Machine Learning for IBM z/OS is IBM’s flagship full-lifecycle platform designed to help organizations build, deploy, manage and operationalize machine learning and deep learning models on z/OS. Built for developers and data scientists, this platform is a watsonx.ai extension for z/OS and is designed to support faster development, deployment and monitoring of machine learning models. In IBM’s view, organizations must be clear about how their AI models are trained, what data is used in that training and what goes into an AI model’s recommendations. Today, clients can implement trustworthy AI capabilities on IBM Z through IBM Cloud Pak for Data capabilities, helping to ensure models and workflows are transparent and explainable. In the coming months, IBM plans to roll out these capabilities natively for workloads on IBM z/OS.
- Cloud Pak for Data on IBM Z: This is an enhanced, powerful Auto AI tool within Cloud Pak for Data 4.7 for automating the process of building machine learning models. It allows users to upload their data, choose the problem type, specify constraints and run a series of automated experiments that generate a range of high-performing pipelines quickly and easily.
- AI-infused IBM z/OS 3.1: Generally available on September 29, 2023, IBM z/OS 3.1 represents a new era in operating system intelligence. Using the new AI System Services for IBM z/OS, the system is designed to learn and predict how to optimize IT processes, simplify management, improve performance and reduce special skills requirements.
IBM Z Supports the Entire AI Lifecycle
There’s a lot of innovation happening with generative AI, including the recently announced IBM watsonx Code Assistant for Z—a new generative-AI-assisted product for mainframe application modernization that will help enable faster translation of COBOL to Java on IBM Z and enhance developer productivity on the platform.
However, for many businesses, the first step to deriving value from AI today means focusing on the entire AI lifecycle, which also includes the fine-tuning, inferencing and deployment of machine learning and deep learning models. For companies to make the most of their AI investments, IBM believes that they need to tap into their mission-critical data. IBM z16 is designed to score business transactions at scale delivering the capacity to process up to 300B deep learning inference requests per day with 1ms of latency. This scale opens significant opportunities for AI use cases on the mainframe, such as fraud detection, anti-money laundering, clearing and settlement, healthcare and application modernization.
Source: Elpida Tzortzatos and Meeta Vouk, IBM