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AI, hybrid cloud and SAP - more than chat

AI and ML are trending topics par excellence, including in the SAP area. However, the development, provision and management of AI and ML models are associated with a number of challenges and require specific frameworks.
Peter Körner, Red Hat
December 14, 2023
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This text has been automatically translated from German to English.

The AI and ML models are associated with a number of challenges and require specific frameworks and tools. Here too, support is provided by an established, open hybrid cloud platform and an ecosystem toolchain.

Not least due to the hype surrounding ChatGPT and LLM (Large Language Model), AI and ML are becoming increasingly relevant in many companies, including SAP users. SAP itself is increasingly going down the AI route, as the announcement of the new digital assistants based on generative AI shows.

However, the range of applications for AI in the SAP context goes far beyond the possibilities of a voice assistant. Efficient use is also becoming increasingly useful in master data analysis, the optimization of production processes and supply chains or quality control, for example. Many companies are also increasingly developing and training models with SAP data, which they then use and operate in a wide variety of productive environments such as factory and edge scenarios.

An ideal MLOps basis for model development, model serving and monitoring as well as lifecycle management and data science pipelines for the entire company in the context of SAP and non-SAP data sources is an open hybrid cloud platform. Firstly, it offers users access to certified AI/ML partners as part of an ecosystem. For companies, this means that they receive complete solutions for the development, provision and management of ML models and can therefore use AI-supported, intelligent applications more easily and quickly.

With Red Hat OpenShift Data Science, such an open source MLOps platform is available both as a managed service and as a traditional software product in the cloud and on-premises. A cloud-native runtime environment as a basis supports AI integrations in hybrid, on-premises and edge environments alike - and therefore also different customer and application-specific requirements. This flexibility is a major advantage, especially when it comes to AI. On the one hand, companies can develop and train AI models with confidential data in their own data center and then operate them in a controlled manner in applications and in the cloud. On the other hand, it is also possible to use the cloud for the development and training of AI models, for example using anonymized or synthetic test data, and then integrate the models into an on-premises application or at the edge.

The use of AI promises many advantages, especially with regard to supply chain optimization or saving resources to achieve sustainability goals. But an area such as automation can also benefit significantly. For example, a company can use AI to train automation with regard to its own infrastructure. This makes it possible to design new user-specific use cases more quickly. In the field of automation, Red Hat is also increasingly focusing on the topic of AI, as demonstrated by the Red Hat Ansible Lightspeed solution with the IBM Watsonx Code Assistant for AI-driven IT automation. It is aimed at the AI-generated creation of playbooks. This means that based on AI-generated recommendations, a syntactically correct code, adapted to your own IT landscape, is output. Even complex, cross-silo automation scenarios can be implemented more quickly.

There is no question that the use of AI/ML techniques will increase across the board. However, the initial training of AI models is very infrastructure-intensive and requires specialized platforms, frameworks and tools, even before model serving, tuning and model management are addressed. With Red Hat OpenShift Data Science, Red Hat provides a consistent, scalable foundation for IT operations and a partner ecosystem for data scientists and developers, so that innovations in the field of AI can also be used more easily and quickly by SAP users.

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Peter Körner, Red Hat

Peter Körner is Principal Business Development Manager Red Hat SAP Solutions at Red Hat


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Work on SAP Basis is crucial for successful S/4 conversion. This gives the so-called Competence Center strategic importance among SAP's existing customers. Regardless of the operating model of an S/4 Hana, topics such as automation, monitoring, security, application lifecycle management, and data management are the basis for the operative S/4 operation. For the second time already, E3 Magazine is hosting a summit in Salzburg for the SAP community to get comprehensive information on all aspects of S/4 Hana groundwork. With an exhibition, expert presentations, and plenty to talk about, we again expect numerous existing customers, partners, and experts in Salzburg. E3 Magazine invites you to Salzburg for learning and exchange of ideas on June 5 and 6, 2024.

Venue

Event Room, FourSide Hotel Salzburg,
At the exhibition center 2,
A-5020 Salzburg

Event date

June 5 and 6, 2024

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Early Bird Ticket - Available until 29.03.2024
EUR 440 excl. VAT
Regular ticket
EUR 590 excl. VAT

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Venue

Event Room, Hotel Hilton Heidelberg,
Kurfürstenanlage 1,
69115 Heidelberg

Event date

28 and 29 February 2024

Tickets

Regular ticket
EUR 590 excl. VAT
The organizer is the E3 magazine of the publishing house B4Bmedia.net AG. The presentations will be accompanied by an exhibition of selected SAP partners. The ticket price includes the attendance of all lectures of the Steampunk and BTP Summit 2024, the visit of the exhibition area, the participation in the evening event as well as the catering during the official program. The lecture program and the list of exhibitors and sponsors (SAP partners) will be published on this website in due time.