The Role of Large Language Models in Internet Product Design and Operations: Focus on Generation, Tuning, and Operational Efficiency

This report focuses on the role of large language models [LLMs] in the design and operation of internet products, with a particular emphasis on their applications in content generation and model optimization, as well as their contribution to improving operational efficiency. It also looks ahead to the AI4S [AI for Science] related models in the fields of management science and scientific learning for the next three years. The report begins by briefly describing the technical foundation of LLMs, analyzing their roles in assisting with the generation of UI/UX components and optimizing design plans in product design, as well as their applications in automating testing, providing personalized user experiences, and enhancing resource management efficiency in operation. It also elaborates on optimization techniques such as LoRA and QLoRA. Finally, it looks forward to future trends such as the combination of AI4S with multi-agent systems, providing strategic references for product teams.

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Publication Details

Journal
Future of Social Sciences
Published
2025-09-09
DOI
https://doi.org/10.64613/fss.5
Primary Topic
Semantic Web and Ontologies
Type
article
Field-Weighted Citation Impact
0.00
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article

The Role of Large Language Models in Internet Product Design and Operations: Focus on Generation, Tuning, and Operational Efficiency

Jiahui Li
Future of Social Sciences
Semantic Web and Ontologies
article

The Role of Large Language Models in Internet Product Design and Operations: Focus on Generation, Tuning, and Operational Efficiency

Jiahui Li
article en

Abstract

This report focuses on the role of large language models [LLMs] in the design and operation of internet products, with a particular emphasis on their applications in content generation and model optimization, as well as their contribution to improving operational efficiency. It also looks ahead to the AI4S [AI for Science] related models in the fields of management science and scientific learning for the next three years. The report begins by briefly describing the technical foundation of LLMs, analyzing their roles in assisting with the generation of UI/UX components and optimizing design plans in product design, as well as their applications in automating testing, providing personalized user experiences, and enhancing resource management efficiency in operation. It also elaborates on optimization techniques such as LoRA and QLoRA. Finally, it looks forward to future trends such as the combination of AI4S with multi-agent systems, providing strategic references for product teams.

Future of Social SciencesVol. 1(1)
Openalex Percentile: Top 87%
Semantic Web and Ontologies
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