BioinspiredLLM: Conversational Large Language Model for the Mechanics of Biological and Bio-inspired Materials
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The study of biological materials and bio-inspired materials science is well established; however, surprisingly little knowledge has been systematically translated to engineering solutions. To accelerate discovery and guide insights, an open-source autoregressive transformer large language model, BioinspiredLLM, is reported. The model was finetuned with a corpus of over a thousand peer-reviewed articles in the field of structural biological and bio-inspired materials and can be prompted to actively and interactively recall information, assist with research tasks, and function as an engine for creativity. The model has proven by example that it is not only able to accurately recall information about biological materials when queried but also formulate biomaterials questions and answers that can evaluate its own performance. BioinspiredLLM also has been shown to develop sound hypotheses regarding biological materials design and remarkably so for materials that have never been explicitly studied before. Lastly, the model showed impressive promise in collaborating with other generative artificial intelligence models in a workflow that can reshape the traditional materials design process. This collaborative generative artificial intelligence method can stimulate and enhance bio-inspired materials design workflows. Biological materials is at a critical intersection of multiple scientific fields and models like BioinspiredLLM help to connect knowledge domains.
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