Imitation of Life: A Search Engine for Biologically Inspired Design
Research output: Contribution to journal › Conference article › Research › peer-review
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Imitation of Life : A Search Engine for Biologically Inspired Design. / Emuna, Hen; Borenstein, Nadav; Qian, Xin; Kang, Hyeonsu; Chan, Joel; Kittur, Aniket; Shahaf, Dafna.
In: Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 38, No. 11, 2024, p. 503-511.Research output: Contribution to journal › Conference article › Research › peer-review
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TY - GEN
T1 - Imitation of Life
T2 - 38th AAAI Conference on Artificial Intelligence, AAAI 2024
AU - Emuna, Hen
AU - Borenstein, Nadav
AU - Qian, Xin
AU - Kang, Hyeonsu
AU - Chan, Joel
AU - Kittur, Aniket
AU - Shahaf, Dafna
N1 - Publisher Copyright: Copyright © 2024, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
PY - 2024
Y1 - 2024
N2 - Biologically Inspired Design (BID), or Biomimicry, is a problem-solving methodology that applies analogies from nature to solve engineering challenges. For example, Speedo engineers designed swimsuits based on shark skin. Finding relevant biological solutions for real-world problems poses significant challenges, both due to the limited biological knowledge engineers and designers typically possess and to the limited BID resources. Existing BID datasets are hand-curated and small, and scaling them up requires costly human annotations. In this paper, we introduce BARCODE (Biological Analogy Retriever), a search engine for automatically mining bio-inspirations from the web at scale. Using advances in natural language understanding and data programming, BARCODE identifies potential inspirations for engineering challenges. Our experiments demonstrate that BARCODE can retrieve inspirations that are valuable to engineers and designers tackling real-world problems, as well as recover famous historical BID examples. We release data and code; we view BARCODE as a step towards addressing the challenges that have historically hindered the practical application of BID to engineering innovation.
AB - Biologically Inspired Design (BID), or Biomimicry, is a problem-solving methodology that applies analogies from nature to solve engineering challenges. For example, Speedo engineers designed swimsuits based on shark skin. Finding relevant biological solutions for real-world problems poses significant challenges, both due to the limited biological knowledge engineers and designers typically possess and to the limited BID resources. Existing BID datasets are hand-curated and small, and scaling them up requires costly human annotations. In this paper, we introduce BARCODE (Biological Analogy Retriever), a search engine for automatically mining bio-inspirations from the web at scale. Using advances in natural language understanding and data programming, BARCODE identifies potential inspirations for engineering challenges. Our experiments demonstrate that BARCODE can retrieve inspirations that are valuable to engineers and designers tackling real-world problems, as well as recover famous historical BID examples. We release data and code; we view BARCODE as a step towards addressing the challenges that have historically hindered the practical application of BID to engineering innovation.
U2 - 10.1609/aaai.v38i1.27805
DO - 10.1609/aaai.v38i1.27805
M3 - Conference article
AN - SCOPUS:85189348972
VL - 38
SP - 503
EP - 511
JO - AAAI Conference on Artificial Intelligence
JF - AAAI Conference on Artificial Intelligence
SN - 2159-5399
IS - 11
Y2 - 20 February 2024 through 27 February 2024
ER -
ID: 390579448