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How can LLMs transform the robotic design process?

We show that large language models (LLMs), such as ChatGPT, can guide the robot design process, on both the conceptual and technical level, and we propose new human–AI co-design strategies and their societal implications.

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Fig. 1: Design pipeline.
Fig. 2: An AI model designed this robotic gripper.
Fig. 3: Opportunities and risks of human–LLM design collaboration.


  1. Brants, T., Popat, A. C., Xu, P., Och, F. J. & Dean, J. In Proc. 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL) 858–867 (ACM, 2007).

  2. Budzianowski, P. & Vulić, I. Preprint at (2019).

  3. Brohan, A. et al. In Conference on Robot Learning 287–318 (PMLR, 2023).

  4. Huang, W., Abbeel, P., Pathak, D. & Mordatch, I. Preprint at (2022).

  5. Wei, J. et al. Preprint at (2022).

  6. Floridi, L. & Chiriatti, M. Minds Mach. 30(4), 681–694 (2020).

    Article  Google Scholar 

  7. Chen, M. et al. Preprint at (2021).

  8. Wolfram, S. Stephen Wolfram Writings (2023).

  9. Ramesh, A. et al. Preprint at (2022).

  10. Shanahan, M. Preprint at (2022).

  11. Stokel-Walker, C. Nature 613, 620–621 (2023).

    Article  Google Scholar 

  12. Vincent, J. The Verge (2023).

  13. George, A. & Walsh, T. Nat. Mach. Intell. 4, 1057–1060 (2022).

    Article  Google Scholar 

  14. Anonymous. Nat. Mach. Intell. 5, 1 (2023).

    Article  Google Scholar 

  15. Stella, F. & Hughes, J. Front. Robot. AI 9, 1059026 (2023).

    Article  Google Scholar 

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Correspondence to Francesco Stella.

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Nature Machine Intelligence thanks David Howard for their contribution to the peer review of this work.

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Stella, F., Della Santina, C. & Hughes, J. How can LLMs transform the robotic design process?. Nat Mach Intell 5, 561–564 (2023).

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