In the rapidly evolving landscape of technology, the symbiosis between traditional computing platforms and innovative Artificial Intelligence (AI) capabilities has become not just a trend but a necessity. As organizations and individuals seek to harness the power of AI for optimizing workloads, the marriage of Linux and AI emerges as a compelling frontier.

This IBM® Redpaper publication discusses the technical intricacies of AI and Machine Learning (ML) within the robust IBM Z® ecosystem, exploring the synergy between Linux-based systems and the transformative potential of AI. It extends into the technical intricacies of integrating AI-enhanced workloads, shedding light on security concerns, and projecting the transformative impact of AI across industries.

This exploration encompasses fundamental technical principles, addressing critical aspects of setup, including hardware configurations, software prerequisites, and the nuances of Linux deployment. Readers will gain insights into the technical advantages inherent in leveraging Linux on IBM Z, particularly with the advancements introduced by the IBM z16™. Case studies dissecting various AI applications in Linux workloads on IBM Z, spanning supervised and unsupervised learning, natural language processing, and time series analysis will be discussed. Nuanced technical discussions cover performance metrics, security considerations, and future trajectories associated with the IBM Telum® processor-a linchpin in advancing AI and ML hardware innovation, are also included.

As we delve into the realms of automation, machine learning, and deep learning, the fusion of these two powerful domains unfolds as a catalyst for innovation and efficiency. As we navigate through the enriching landscape of Linux and AI convergence, the goal of this publication is that it serves as a valuable resource, inspiring you to leverage the synergies between these two dynamic domains. Whether you are seeking to optimize workloads, build intelligent systems, or simply explore the limitless possibilities at the intersection of Linux workloads and AI, this publication endeavors to be your companion on this innovative journey.

This IBM Redpaper publication is intended for data scientists, Chief Data Officers, and infrastructure personnel looking to leverage existing AI models in a Linux on Z environment without requiring deep knowledge in IBM Z, exploit the AI accelerator, as much and as easily as possible, for models running on Z, gain insights from data in place while remaining secure and compliant, and simplify the AI software installation pipeline keeping your AI software stack up-to-date with the latest versions and capabilities.

Chapter 1. Introduction to AI and Machine Learning

Chapter 2. Getting started with AI on Linux for IBM Z

Chapter 3. The power of Linux on Z for AI workloads

Chapter 4. AI case studies for Linux workloads on IBM Z

Chapter 5. AI Model inferencing on IBM Z

Chapter 6. Security and privacy

Chapter 7. Future trends