Generative Artificial Intelligence Device to analysis the data for SAP based Data Management

A table-native AI model that shortens time-to-value for predictive activities on tabular data is being built by SAP. It is called the SAP Foundation Model. The goal is to build a general-purpose prediction engine that can automatically generate predictions from tabular data with minimal or no more training data. Although LLMs excel at text generation, they struggle with business-related data that is tabular and has challenges with categorisation, regression, and prediction. In fact, the SAP Foundation Model can compete with and even surpass these conventional methods while providing the flexibility of foundation models; in contrast, state-of-the-art LLMs perform 20-50% worse than incumbent restricted AI approaches in comparable cases. SAP has a long track record of successfully meeting business needs, and the company's stated goal is to develop AI that is useful, trustworthy, and socially conscious so that it can assist clients in solving their business challenges. Another innovative strategy for AI development, federated learning is quickly becoming the standard for delivering AI apps to the periphery of industrial networks. Research into the development of ethical guidelines and frameworks for the deployment of AI in MIS should prioritize the safety and security of data. In order to reap the benefits of AI integration for businesses, one must first establish a cohesive digital business plan. Another is getting people to interact with AI despite obstacles.

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Publication Details

Published
2024-11-23
DOI
https://doi.org/10.1109/icec59683.2024.10837215
Citations
3
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
1.59
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article

Generative Artificial Intelligence Device to analysis the data for SAP based Data Management

Harish Narne
3 citations
Big Data and Business Intelligence
1.59
article

Generative Artificial Intelligence Device to analysis the data for SAP based Data Management

Harish Narne
article en
3 citations

Abstract

A table-native AI model that shortens time-to-value for predictive activities on tabular data is being built by SAP. It is called the SAP Foundation Model. The goal is to build a general-purpose prediction engine that can automatically generate predictions from tabular data with minimal or no more training data. Although LLMs excel at text generation, they struggle with business-related data that is tabular and has challenges with categorisation, regression, and prediction. In fact, the SAP Foundation Model can compete with and even surpass these conventional methods while providing the flexibility of foundation models; in contrast, state-of-the-art LLMs perform 20-50% worse than incumbent restricted AI approaches in comparable cases. SAP has a long track record of successfully meeting business needs, and the company's stated goal is to develop AI that is useful, trustworthy, and socially conscious so that it can assist clients in solving their business challenges. Another innovative strategy for AI development, federated learning is quickly becoming the standard for delivering AI apps to the periphery of industrial networks. Research into the development of ethical guidelines and frameworks for the deployment of AI in MIS should prioritize the safety and security of data. In order to reap the benefits of AI integration for businesses, one must first establish a cohesive digital business plan. Another is getting people to interact with AI despite obstacles.

Openalex Percentile: Top 12%
Big Data and Business Intelligence
1.59
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