Summary of Generative Ai and Process Systems Engineering: the Next Frontier, by Benjamin Decardi-nelson et al.
Generative AI and Process Systems Engineering: The Next Frontier
by Benjamin Decardi-Nelson, Abdulelah S. Alshehri, Akshay Ajagekar, Fengqi You
First submitted to arxiv on: 15 Feb 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI); Systems and Control (eess.SY); Optimization and Control (math.OC)
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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 The article explores how generative artificial intelligence (GenAI) models can enhance solution methodologies within process systems engineering (PSE). Large language models (LLMs) and foundation models (FMs), pre-trained on extensive datasets, offer versatility for tasks like query response, image generation, and decision-making. The synergy between GenAI and PSE is crucial due to advancements in computing and systems technologies. The paper begins by overviewing classic and emerging GenAI models, including FMs, before delving into their applications within key PSE domains: synthesis, optimization, and process monitoring. It discusses potential advances in PSE methodologies and identifies challenges like multiscale modeling, data requirements, evaluation metrics, trust, and safety. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper looks at how new artificial intelligence (AI) models can help solve problems in a field called process systems engineering (PSE). These AI models are really good at doing tasks like answering questions, making images, and making decisions. The article explains how these models can be used to make PSE better by looking at three main areas: designing and building processes, optimizing processes, and monitoring and controlling them. It also talks about some of the challenges that come with using AI in PSE, like needing more data and coming up with good ways to measure success. |
Keywords
* Artificial intelligence * Image generation * Optimization
