Business and operational security in the context of Artificial Intelligence | SUSE Communities

Business and operational security in the context of Artificial Intelligence


This is a guest blog by Udo Würtz, Fujitsu Fellow, CDO and Business Development Director of the Fujitsu’s European Platform Business. Read more about Udo, including how to contact him, below.


Deploying AI systems in an organization requires significant investments in technology, talent, and training. There is a fear that the expected ROI (return on investment) will not materialize, especially if the deployment does not meet business needs.

This is where a reference architecture like the AI Test Drive comes into play. It allows companies to test the feasibility and return on investment of AI solutions in a controlled environment before committing to significant investments. AI Test Drive thus addresses not only technical risks, but also commercial risks, enabling companies to make informed decisions.

The field of data science is rapidly evolving, and many professionals are looking for a reliable platform to effectively evaluate AI applications. However, such architectures must support a range of cutting-edge technologies. So let’s examine each technology component and its importance in this context.

  1. Platform and Cluster Management with SUSE Rancher:

Kubernetes has become the gold standard for container orchestration. Rancher, a comprehensive Kubernetes management tool, supports the operations and scalability of AI models. It allows the management of Kubernetes clusters across multiple cloud environments, simplifying the roll-out and management of AI applications.

  1. Hyper-convergence with Harvester:

In contemporary AI environments, which are usually cloud native environments, the capacity for hyper-convergence—integrating computation, storage, and networking into one solution—is invaluable. Harvester offers this capability, leading to enhanced efficiency and scalability for AI applications.

  1. Computational Power through Intel:

Intel technologies, notably the Intel® Xeon® Scalable processors, are fine-tuned for AI applications. Additional features like the Intel® Deep Learning Boost accelerate deep learning tasks. In particular, the Gen 4 has separate AI accelerators on board, which makes this type of Processor significantly different from the previous ones and delivers incredible performance. In a project involving vehicle detection, the Gen 3 had an inference of 30 frames / s. This was a very good performance. Gen 4 of over 5000(!) frames/s, due to the accelerators inside the chip.

  1. Storage Solutions with NetApp:

Data is the core of AI. NetApp provides efficient storage solutions specially designed to store and process massive datasets, which is crucial for AI projects.

  1. Parallel Processing with NVIDIA:

The parallel processing capability that NVIDIA GPUs bring to the table is invaluable in AI applications where large datasets must be processed simultaneously. 

  1. Network Infrastructure by Juniper:

The backbone of every AI platform is its networking. Juniper delivers advanced network solutions ensuring efficient, bottleneck-free data traffic flow. This is vital in AI settings where there are demands for low latency and high bandwidth.

Now You Can Evaluate Your AI Projects Practically & Technically:

The Fujitsu AI Test Drive amalgamates tried-and-true technologies into a cohesive platform, granting data scientists the ability to evaluate their AI projects both pragmatically and technically. By accessing such deep technological resources, users can pinpoint the tools and infrastructure that best align with their unique AI challenges.

Share your idea and we share knowledge and resources.

What is your vision for a business model that fully exploits the possibilities of innovative IT concepts? Do you already have a vision that you are implementing concretely? Or do you still lack the necessary resources on the way from the idea to realization, for example technical expertise, budget and sufficient test capacities?

We’re pleased to introduce the Fujitsu Lighthouse Initiative, a special program, designed to foster prototyping and drive technological endeavors, ensuring businesses harness the full potential of emerging technologies.​ The initiative isn’t just about gaining support for your Digital Innovation and prototyping projects; it’s a pathway to joint project realization. Selected projects can benefit from a project support pool of €100,000, to be used tailored to these project’s unique requirements. Together, we will leverage Fujitsu’s resources, expertise, and vast ecosystem to turn visionary ideas into tangible outcomes.

Register today for the Fujitsu Lighthouse Initiative.


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About the Author:

Udo Würtz is Chief Data Officer ( CDO of the Fujitsu European Platform Business. In his function he advises customers at C level (CIO, CTO, CEO, CDO, CFO) on strategies, technologies and new trends in the IT business. Before joining Fujitsu, he worked for 17 years as CIO for a large retail company and later for a Cloud Service Provider, where he was responsible for the implementation of secure and highly available IT architectures. Subsequently, he was appointed by the Federal Ministry of Economics and Technology as an expert for the Trusted Cloud Program of the Federal Government in Berlin. Udo Würtz is intensively involved in Fujitsu’s activities in the fields of artificial intelligence (AI), container technologies and the Internet of Things (IoT) and, as a Fujitsu Fellow, gives lectures and live demos on these topics. He also runs his own YouTube channel on the subject of AI.

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Miriam Kang Partner Marketing Director, SUSE