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AI and biodiversity both thrive on complexity. For AI, massive amounts of data fuel machine learning models, helping them to recognise patterns, make predictions and solve problems. In most cases, the richer and more diverse the data, the smarter and more adaptive AI becomes.
Early indications suggest that ambition might surpass success. Signatories were expected to submit national biodiversity strategies and action plans before the start of the conference. Only 25 out of 195 countries filed plans to the UN Biodiversity Secretariat – and just five of 17 “megadiverse countries,” which are home to about 70% of the world’s biodiversity, have offered their pledges.
Adam Thompson, global sustainable finance and ESG offering leader at IBM Consulting, has seen firsthand how AI can transform how countries handle, process and understand information. Though it presents its own challenges when it comes to energy consumption, Generative AI offers a potential path for making data processing easier without stakeholders needing all of the data on hand.
The elephants are known for clearing out vegetation, making room for stronger and more resilient flora to thrive in an environment that would otherwise have its resources strained by overgrowth and competition.
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