Summary of The Systems Engineering Approach in Times Of Large Language Models, by Christian Cabrera et al.
The Systems Engineering Approach in Times of Large Language Models
by Christian Cabrera, Viviana Bastidas, Jennifer Schooling, Neil D. Lawrence
First submitted to arxiv on: 13 Nov 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computers and Society (cs.CY); Software Engineering (cs.SE)
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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 novel technology, Large Language Models (LLMs), aims to address critical societal problems by integrating it into socio-technical systems. However, the complexity of these systems and the nature of LLMs challenge this vision. The paper highlights that rather than relying on Artificial Intelligence (AI) alone, a Systems Engineering approach is more effective in facilitating the adoption of LLMs by prioritizing problems and their context over other aspects. The research surveys existing efforts to engineer AI-based systems and reveals how systems engineering principles can address similar issues posed by LLMs, providing future directions for adopting this technology. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary LLMs aim to help with big societal problems. But it’s hard to make them work because of the complexity of these problems and the way LLMs are designed. Instead of just relying on AI experts, we need a different approach that considers what needs to be solved first. This paper looks at how systems engineering can help us adopt LLMs by prioritizing what needs to be done before anything else. It’s like building a bridge – you need to figure out where the bridge will go and what it will look like before you start constructing it. |
