Regulatory Challenges and Optimization Strategies for Open Large Language Models: A Multidimensional Framework for Efficient Management Chapter in Scopus uri icon

abstract

  • Innovations in artificial intelligence are rapidly transforming various industries, particularly through the development and deployment of Open Large Language Models (OLLMs). However, the absence of a robust regulatory framework presents significant challenges in ensuring the ethical, safe, and effective use of these models. This research aims to address this gap by proposing a comprehensive regulatory framework designed to optimize the scalability and performance of OLLMs, emphasizing the importance of structured pruning techniques. By integrating both quantitative and qualitative analyses, the study will assess the technical capabilities and societal implications of OLLMs, ultimately providing clear guidelines that promote responsible and sustainable innovation. The expected outcomes include the development of a governance model that balances the need for innovation with ethical considerations, offering a pathway for the regulation of OLLMs that supports their continued evolution while safeguarding public interests. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

publication date

  • January 1, 2025