Summary of Towards Automated Solution Recipe Generation For Industrial Asset Management with Llm, by Nianjun Zhou et al.
Towards Automated Solution Recipe Generation for Industrial Asset Management with LLM
by Nianjun Zhou, Dhaval Patel, Shuxin Lin, Fearghal O’Donncha
First submitted to arxiv on: 26 Jul 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper presents a novel approach to Industrial Asset Management (IAM) by integrating Conditional-Based Management (CBM) principles with Large Language Models (LLMs). The authors introduce an automated model-building process, which traditionally relies on collaboration between data scientists and domain experts. Two key innovations are presented: a taxonomy-guided prompting generation that enables the automatic creation of AI solution recipes and LLM pipelines designed to produce solution templates for heterogeneous asset classes without human input. These pipelines, guided by standardized principles, enhance automation and reduce reliance on extensive domain knowledge. The methodology is evaluated across ten asset classes, demonstrating the potential of LLMs and taxonomy-based prompting pipelines in transforming asset management. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study shows how to make Industrial Asset Management (IAM) better using artificial intelligence (AI). Right now, building AI models for different types of assets requires a lot of work and expertise from both data scientists and domain experts. The authors developed a new way to automate this process by using large language models and special prompts. This approach can help reduce the need for human involvement and make it easier to manage different types of assets. The study tested this method on ten different asset classes and showed that it has the potential to improve IAM. |
Keywords
» Artificial intelligence » Prompting
