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What is Artificial Intelligence?
In simple terms, Artificial Intelligence (AI) refers to systems or solutions that can replicate human decision-making capabilities. These solutions often leverage a combination of software and hardware to mimic human capabilities like problem -solving and decision making.
AI Enabled Applications in SAP Portfolio
SAP applications leverage AI and ML algorithms extensively to either embed innovative capabilities within their solutions, help end-users perform advanced analytics with minimal technical proficiency, or allow data scientists and ML engineers to build advanced ML models and solutions. SAP HANA has been designed to be easily leveraged as a scalable ML platform. A powerful in-built tool is the Predictive Analytics Library (PAL). SAP data intelligence has a rich ML content library. Like most best-of-breed analytics tools, SAP Analytics Cloud provides users the ability to leverage advanced Machine Learning (ML) algorithms. While ML algorithms have many applications, predictive analytics remains a key one.
What is Artificial Intelligence?
In simple terms, Artificial Intelligence (AI) refers to systems or solutions that can replicate human decision-making capabilities. These solutions often leverage a combination of software and hardware to mimic human capabilities like problem -solving and decision making.
AI Enabled Applications in SAP Portfolio
SAP applications leverage AI and ML algorithms extensively to either embed innovative capabilities within their solutions, help end-users perform advanced analytics with minimal technical proficiency, or allow data scientists and ML engineers to build advanced ML models and solutions. SAP HANA has been designed to be easily leveraged as a scalable ML platform. A powerful in-built tool is the Predictive Analytics Library (PAL). SAP data intelligence has a rich ML content library. Like most best-of-breed analytics tools, SAP Analytics Cloud provides users the ability to leverage advanced Machine Learning (ML) algorithms. While ML algorithms have many applications, predictive analytics remains a key one.
On the business processes side, SAP AI offering promises to infuse transformative intelligence to all key business processes areas like lead to cash, design to operate, source to pay and recruit to retire. AI algorithms help include innovative features across all these processes.
Key Considerations for SAPinsiders
- Develop a fundamental understanding of AI algorithms: Explore what specific algorithms are available and understand where they can be leveraged. This will help you get optimal value from these tools. As an example, you should be aware that you can use clustering algorithms for customer segmentation. Here is an example of a good overview of critical algorithms used in SAP applications.
- Understand the limitations of underlying data infrastructure: Understanding aspects of the underlying database is also critical. This helps you build pragmatic models. As an example, HANA has a 2 billion rows limitation, and hence you may have to leverage partitioning of tables for data larger than that. This impacts your model development as well.
- Understand the limitations of tools available: Understanding the ML tools’ limitations is another aspect that saves you a lot of pain. For example, some PAL algorithms have limits on the number of parameters. This means you will have to pay more attention to feature selection or feature engineering while building models with these algorithms. You can find several examples of these limitations on the SAP help portal and SAP blogs.
107 results
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Overcoming Contract Backlogs with AI
Reading time: 2 mins
Managing contracts is one of the key areas that is ripe for process automation. Companies can no longer rely on manual methods to manage their contracts, as they risk missing out on key compliance requirements. Additionally, as companies grow larger, the process of manually combing through each agreement is no longer scalable or even sustainable.…
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Demystifying AI with Deloitte
Reading time: 2 mins
AI is still an emerging field, with new capabilities and solutions constantly making their way into the SAP landscape. While it may be tempting to wait until AI technology is perfected, organizations that wait on the sideline risk being left behind. By bringing together thought leadership, easily-implemented microsolutions, and a platform to deliver business transformation,…
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- SAP AI
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Kick-start your AI development with GenAI Hub
Click Here to View the Session Deck Join us as we get under the hood of AI Core access service, enabling developers to interact with AI models directly, and demonstrate how developers can create and manage prompts for their AI models. We will show you Additionally, understand how to deliver advanced language model interaction patterns…...…
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- SAP AI
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Turbo-Charging Unstructured Data Processing to Boost Efficiency
Click Here to View the Session Deck Deep dive into SAP Document Information Extraction and how generative AI is streamlining processes and increasing process-related efficiency. We will explore schema-based extraction of unstructured data, support for 40+ languages, and provide a roadmap to what you can look forward to in 2024. You will: Gain insights into…...…
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- SAP AI
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Six Key Things to Learn from Gen AI Related Initiatives
Click Here to View the Session Deck The session delves into the diverse options available for building and deploying Gen AI solutions, ranging from proprietary platforms to open-source frameworks. The discussion also emphasizes the critical aspect of interoperability between SAP Gen AI offerings and the broader open-source community. Additionally, you explore strategies to unlock greater…...…
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- SAP AI
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How the SAP AI Core Toolkit for VS Code Simplifies Your AI Development
Click Here to View the Session Deck With the SAP AI Core Toolkit for VS Code you will be able to connect and manage all steps involved in your AI use case in one place. In this session you will learn how to implement a custom AI use case in SAP AI Core using the…...…
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AI in Liquidity Management: How It Can Assist a Liquidity Manager
Reading time: 3 mins
Artificial intelligence and machine learning (AI/ML) are emerging treasury technology that have become essential for cash flow forecasting, payments fraud prevention and liquidity management. But is treasury on board and ready for AI in liquidity management? The Difference between ML and AI AI and ML are not technically the same thing. AI is a broad term denoting intelligent machines that can…
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- SAP AI
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How to Implement a RAG Use Case With The Generative AI Hub on SAP AI Core
Click Here to View the Session Deck In this session you will learn how to include large language models into your application. You will learn how to use custom documents to perform Retrieval Augmented Generation for Question-Answering to customize the models’ responses to your needs. The use case will be implemented using the Python SDK…...…
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- SAP AI
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SAP BTP and the AI Horizon: Shaping Tomorrow’s Intelligent Enterprise
Click Here to View the Session Deck In the fast-evolving business landscape, enterprises are faced with the challenge of harnessing cutting-edge technologies to drive innovation and stay ahead of the curve. Join us in this insightful keynote as we explore the pivotal role of SAP Business Technology Platform (BTP) in shaping the future of intelligent…...…
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- SAP AI
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How AI will Help in The Future to Achieve High-Effective SAP Quality Engineering
Click Here to View the Session Deck For decades, the concept of Artificial Intelligence (AI) has captivated our imaginations – from science fiction and film to algorithms that can approximate conversation, to the predictive text programs that can produce new Harry Potter fan fiction today. AI is no longer a concept, it is real and…...…
Featured Insiders
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Nathan Williams
Director, Development & Innovation. NIMBL
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Hari Sonnenahalli
NTT DATA, Enterprise Architecture
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Damien Johnson
Global Chief Architect - RISE Ecosystems, SAP
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