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Unlocking the Power of Generative AI for innovation: Guiding principles for Responsible LLM applications

Author(s) Sibin Thomas
Country United States
Abstract This paper presents five key principles: setting clear goals, focusing on data quality, being open to changes, keeping human involvement, and following responsible AI practices. We also delve into architectural considerations for deploying LLMs, including data storage, model training, API gateways, application layers, and monitoring. We recommend starting with pre-trained models, using rapid engineering, applying transfer learning, and getting feedback to improve the performance of LLMs. There is a strong emphasis on keeping data private and secure, using methods to remove personal information and protect the models. By following these principles, organizations can take advantage of the benefits of generative AI and LLMs while reducing ethical and security risks. This paper aims to empower organizations to navigate the complexities of LLM adoption and contribute to the responsible development and implementation of these powerful technologies.
Keywords Generative AI, Large Language Models (LLMs), Artificial Intelligence (AI), Machine Learning (ML), AI Adoption, Ethics in AI Responsible AI
Field Engineering
Published In Volume 5, Issue 4, April 2024
Published On 2024-04-09
Cite This Unlocking the Power of Generative AI for innovation: Guiding principles for Responsible LLM applications - Sibin Thomas - IJLRP Volume 5, Issue 4, April 2024. DOI 10.5281/zenodo.14769559
DOI https://doi.org/10.5281/zenodo.14769559
Short DOI https://doi.org/g83ktw

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