How Learning from Nature can Take us Deeper into Space

Learn how the NASA Periodic Table of Life (PeTaL) Project is using artificial intelligence to mine the scientific literature for nature-inspired design.

This is part one of a multi-part series on using artificial intelligence to drive nature-inspired design at NASA. Stay tuned for part two.

Nature-inspired design, also known as biomimicry, is the practice of learning from and emulating nature to solve human design problems. Biomimicry has helped drive human innovation for centuries. Leonardo DaVinci found inspiration for the first ‘flying machine’ by observing birds in flight, and everyday items such as Velcro® were created by mimicking nature’s inherent functionalities. History is rich with examples of nature’s contributions as a useful and powerful tool for human problem-solving, and biomimicry continues to shape the development of new technologies in fields ranging from manufacturing to space exploration.

So, what can nature teach us about sending people and objects into space, or researching black holes? The truth might surprise you. In fact, NASA has embraced nature-inspired design for decades. One of my favorite NASA innovations? A telescope with the ability to look deeper than ever into space, thanks to a lens design that mimics the features of a moth’s eye. While NASA has been building space telescopes since the 1990s, the common moth you might find circling your porch lights at dusk has seen millions of years of evolutionary success seeing in the dark.

Moths have evolved to successfully hunt at dusk and at night, when limited light is available. In order to maximize light capture, the surface of a moth’s eyes are covered with a regular pattern of microscopic bumps. These structures dramatically minimize light reflection, allowing the moth to absorb as much light as possible and see in the dark. The textured surface also helps to create an effective barrier against dust and dirt.

In spite of its established value, there’s a big problem in the field of biomimicry. Most nature-inspired design comes about by happenstance: A conversation with a colleague in passing, or a well-timed walk in nature. But what if there was a way to strategically search through thousands of nature’s most successful designs and quickly identify the ones best suited to help solve a given problem? This is the aim of the NASA Periodic Table of Life (PeTaL) Project: Building a search tool that uses artificial intelligence (AI) and machine learning (ML) to scan and catalogue decades of scientific literature and highlight millions of design ideas from nature.

Stay tuned for part two of this series, where I discuss how we collected our data and trained our machine learning models.

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