OpenSource alternatives of Generative Artifical Intelligence for SME’s

Authors

  • Róbert Szilágyi Section editorUniversity of Debrecen

DOI:

https://doi.org/10.17700/jai.2024.15.2.733

Keywords:

LLM, SME, KNIME, Ollama, RAG

Abstract

This paper investigates the potential of local Large Language Models (LLMs) for Small and Medium-sized Enterprises (SMEs). While cloud-based LLMs offer powerful capabilities, their associated costs, including subscription fees and token-based pricing, can be prohibitive for many SMEs. This research explores the benefits of developing and deploying custom, local LLM solutions, which offer advantages such as reduced operational costs, enhanced data privacy and security, and greater flexibility for customization and integration. The paper examines viable open-source alternatives to commercial LLMs, including Ollama, Gpt4All, and the integration of LLMs within the data science platform KNIME. Furthermore, it explores techniques for improving LLM performance, such as Retrieval-Augmented Generation (RAG) and Low-Rank Adaptation (LoRA). General properties of local LLM solutions, such as CLI and GUI options and multi-platform support, are also discussed. By embracing local LLM solutions, SMEs can leverage the power of AI while mitigating the challenges associated with cloud-based services. This approach empowers businesses to gain a competitive advantage, enhance operational efficiency, and drive innovation while maintaining control over their data and minimizing costs.

 

Author Biography

Róbert Szilágyi, Section editorUniversity of Debrecen

Róbert Szilágyi (PhD) works at University of Debrecen, Economic Analysis Methodology and Applied Informatics Institute as an assistant professor. His professional areas are mobile internet applications in agriculture, e-learning, multimedia content developing, and e-government. He graduated at the University of Debrecen as an agrobusiness engineer. He received the PhD degree at the University of Debrecen in 2006. He got Business Management MBA at the University of Debrecen in 2008. He worked in several research projects and has more than 10 year experience of computer application in agriculture. He has been the secretary of the Hungarian Association of Agricultural Informatics (HAAI) since 2007. He is member of John von Neumann Computer Society. He has more than 70 publications.

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Published

2025-02-04

How to Cite

Szilágyi, R. (2025). OpenSource alternatives of Generative Artifical Intelligence for SME’s . Journal of Agricultural Informatics, 15(2). https://doi.org/10.17700/jai.2024.15.2.733

Issue

Section

Journal of Agricultural Informatics

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