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Natural sciences (Biology)(2024.03)

2023.03.14 Editor W. M.

The Italian polymath Galileo Galilei famously put forward the concept that ‘Mathematics is the language of nature’. How fitting, then, that we should now be using mathematics in the form of AI to understand and interpret natural processes. The sheer complexity of biological processes–––from the molecular and cellular level right up to entire ecosystems––seems a tailor-made challenge for AI to solve. However, AI models need to be trained before they can be set to task. This training requires generation of vast datasets, which in turn is facilitated by

advances in technology and experimental methods. Perhaps the most well-known application of AI in the biology field is the use of DeepMind’s AlphaFold suite of programs to predict the structure of proteins. Usually, this requires time- and labor-intensive wetlab experiments such as X-ray crystallography and cryo-electron microscopy. Crystallography remains the gold standard for determination of protein structure. However, AlphaFold can provide an excellent prediction for an average-sized protein in just 15-20 seconds, whereas the lab-based approaches take days. At the other end of the biological scale, AI may help us to conserve precious ecosystems and protect endangered species. For example, the non-profit organization, Imazon, developed the Previsia AI platform to help predict where deforestation of the Amazonian rainforest is most likely to occur. Previsia looks for new roads springing up in the jungle, and then correlates their appearance with multiple other geographical, demographic and environmental parameters. Combined with historical records of deforestation, this allows Previsia to score the likelihood of deforestation in a particular area. In another example, Rainforest Connection have harnessed Arbimon, an ‘acoustic AI’ platform that allows organizations and researchers to listen to the all the sounds within a given ecosystem at scale and over time. This facilitates the identification of novel species, and the tracking of their behavior and response to changing environmental conditions (including those with a negative impact, such as deforestation and poaching). If such approaches can be combined with real-time responses from local and national governments to mitigate the environmental threats, we can look to the future of the natural world with a healthy optimism.

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