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Retrieval-Augmented Generation and LLM Agents for Biomimicry Design SolutionsWe present BIDARA, a Bio-Inspired Design And Research Assistant, to address the complexity of biomimicry – the practice of designing modern-day engineering solutions inspired by biological phenomena. Large Language Models (LLMs) have been shown to act as sufficient general purpose task solvers, but they often hallucinate and fail in regimes that require domain-specific and up-to-date knowledge. We integrate Retrieval-Augmented Generation (RAG) and Reasoning-and-Action agents to aid LLMs in avoiding hallucination and utilizing updated knowledge during generation of biomimetic design solutions. We find that incorporating RAG increases the feasibility of the design solutions in both prompting and agent settings, and we use these findings to guide our ongoing work. To the extent of our knowledge, this is the first work that integrates and evaluates Retrieval-Augmented Generation within LLM-generated biomimetic design solutions.
Document ID
20240003594
Acquisition Source
Glenn Research Center
Document Type
Presentation
Authors
Christopher Toukmaji
(University of California, Irvine Irvine, United States)
Allison Tee
(Stanford University Stanford, United States)
Date Acquired
March 25, 2024
Subject Category
Cybernetics, Artificial Intelligence and Robotics
Meeting Information
Meeting: Association for the Advancement of Artificial Intelligence (AAAI) Spring Symposium Series
Location: Stanford, CA
Country: US
Start Date: March 25, 2024
End Date: March 27, 2024
Sponsors: Association for the Advancement of Artificial Intelligence
Funding Number(s)
WBS: 533127.02.70.03
Distribution Limits
Public
Copyright
Public Use Permitted.
Technical Review
NASA Peer Committee
Keywords
biomimicry
biomimetics
large-language-models
chatbot
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