Summary of Ai Assistants For Spaceflight Procedures: Combining Generative Pre-trained Transformer and Retrieval-augmented Generation on Knowledge Graphs with Augmented Reality Cues, by Oliver Bensch et al.
AI Assistants for Spaceflight Procedures: Combining Generative Pre-Trained Transformer and Retrieval-Augmented Generation on Knowledge Graphs With Augmented Reality Cues
by Oliver Bensch, Leonie Bensch, Tommy Nilsson, Florian Saling, Bernd Bewer, Sophie Jentzsch, Tobias Hecking, J. Nathan Kutz
First submitted to arxiv on: 21 Sep 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Human-Computer Interaction (cs.HC)
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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 proposes the design of an intelligent personal assistant called CORE for astronauts on the International Space Station, Lunar Gateway, and beyond. CORE is a reliable and flexible assistant that can operate offline and provide intuitive guidance through audiovisual interactions using augmented reality elements. The authors argue that current IPA designs fall short in meeting these criteria and propose CORE as a solution that combines Knowledge Graphs, Retrieval-Augmented Generation for Generative Pre-Trained Transformer, and Augmented Reality to ensure understanding of procedure steps, reliability, offline availability, and flexibility. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper talks about creating a helpful tool for astronauts in space. The tool is called CORE and it’s like a personal assistant that can help with tasks without needing the internet. It uses special technology to show information in a way that’s easy to understand. The authors think that other tools don’t meet the needs of astronauts, so they’re proposing this new one that combines different approaches. |
Keywords
» Artificial intelligence » Retrieval augmented generation » Transformer
